Voice Clone TTS

The enum values printed on this page are a snapshot. The machine-readable source of truth is the Enum Catalog — where the two disagree, that one wins.

Provide text and a voice (speaker) to synthesize speech in that voice (voice cloning). No file upload required — the input is text.

Create Task

Basics

ItemValue
MethodPOST
Path/task/audio_tts_clone
Content-Typeapplication/json
AuthAuthorization header (pass the API Key directly)

Request Body

FieldTypeRequiredDefaultDescription
textstringYes—Text to synthesize; non-empty, up to 5000 characters
speakerstringYes—Voice code (see "Available Voices" below)
text_langstringNothe voice's languageTarget language (BCP-47, e.g. zh-CN). Usually unnecessary — the voice already determines the language; omit it and the voice's own language is used
output_formatstringNowavOutput audio format: wav or mp3
refreshbooleanNofalseForce re-synthesis (skip the cache) for a fresh take; cloud voices only
speednumberNovoice presetSpeech speed factor (1.0 = normal). The valid range differs per voice — use the speed_range returned by the voice list endpoint; some voices do not support speed control (their speed_range has min and max both 1.0). Out-of-range values are rejected up front: no task is created and nothing is billed
subtitle_formatstringNono subtitlePass srt to also receive a .srt subtitle file (UTF-8, no BOM, LF line endings). Timings come from this run's per-sentence timeline and match the audio exactly; overly long sentences are split into multiple lines for the canvas, and the lines of one sentence share its time span in proportion to their length; no extra charge. Omit it and nothing is generated — the outputs stay exactly as before. srt is currently the only accepted value; anything else returns a parameter error
strip_punctuationbooleanNotruePunctuation stripping, affecting only the text of the bonus .srt subtitle from subtitle_format: stripping is on by default (punctuation looks poor in subtitles) — Chinese , 。 and English , . are replaced with spaces, in-word forms are exempt (decimals 3.5, domains example.com, thousands separators 1,000 stay intact), and all other punctuation (quotes, question marks, exclamation marks, dashes, etc.) is kept; consecutive spaces collapse to one and line edges are trimmed. Timecodes, line counts, the audio, and segments are unchanged. Pass false explicitly to keep punctuation intact
canvasinteger[]No[1080, 1920] (portrait)Output canvas [width, height] as two positive integers, accepted only together with subtitle_format (sending it alone returns a parameter error). Subtitles split overly long sentences into multiple lines for this canvas — portrait splits more finely than landscape; omit it and the portrait default is used, so pass [1920, 1080] explicitly for landscape videos. Affects subtitle line breaks only; the audio and segments are unchanged
text_split_methodstringNovoice preset (usually cut1)How long text is split, effective for self-trained (gpt_sovits) voices only; cloud voices currently ignore it and will reject it after an observation period (date to be announced), so do not send it for cloud voices — cloud voices already produce one sentence per segment, so you do not need this parameter to split sentences. It determines the granularity of segments (subtitles break there first, then overly long sentences are split into lines for the canvas): cut1 = group up to 4 sentences, cut2 = about 50 characters, cut3 = at Chinese full stops, cut4 = at English periods, cut5 = at every punctuation mark (one sentence each), cut0 = no split. Pass cut5 to break subtitles at every sentence end
fragment_intervalnumberNovoice presetPause between sentences, in seconds; effective for Tonghe in-house (gpt_sovits) voices only. Valid range [0.05, 1.0] seconds (inclusive — both endpoints are accepted); out-of-range values return a parameter error and are never silently clamped — no task is created and nothing is billed. ⚠️ Cloud voices return an explicit error if you pass it, which is the opposite of text_split_method above (cloud voices ignore that one) — do not assume from that row that passing this one is merely a no-op. Omit it and the voice's own tuned preset is used; the output is byte-for-byte identical to what it was before this parameter shipped

Available Voices (speaker)

VoiceCode (speaker)Source (engine)GenderLanguagePriceDemoDescription
Tonghe in-house (9) · 5 credits/1K chars
NarratornarratorTonghe in-houseMalezh-CN5 credits/1K charsNoticeably lower in pitch and slower than its sibling voices, with neutral brightness and clarity, moderate intonation and few pauses. Steady and unhurried, suited to content that calls for gravity or a narrative mood, such as history documentary voice-over and classic literature audiobooks, drawing listeners into calm, weighty delivery.
LecturerlecturerTonghe in-houseMalezh-CN5 credits/1K charsA noticeably husky, breathy voice, the least clean of the nine sibling voices, with loudness swings well above most siblings and rich dynamics. Suited to content that wants a genuine, relaxed feel, such as late-night relationship podcasts and story audiobook narration, delivering a slightly weathered, emotionally layered read.
Professor Franprofessor_franTonghe in-houseMalezh-CN5 credits/1K charsThe darkest of the nine sibling voices, with the least high-frequency air: very dark, with almost none of the thin, bright top-end detail found in its brighter or airier siblings. Quick pace and flattish intonation. Suited to steady, direct professional content, with no brightness or breathiness to pull attention away from the information.
Cantonese Sistercantonese_accentTonghe in-houseFemalezh-CN5 credits/1K charsVery little loudness variation, far less dynamic swing than its sibling voices, with pronounced high-frequency air for a thin, bright, clear sound. Suited to steady delivery without obvious emotional swings, such as standardized product descriptions and basic science explainers, conveying information clearly and evenly.
Radio Hostessradio_femaleTonghe in-houseFemalezh-CN5 credits/1K charsMinimal loudness variation and a very slow pace make this the calmest, most soothing of the nine sibling voices: no obvious dynamic swings, every word laid out evenly, unhurried throughout. A bright, pure timbre with built-in clarity. Suited to content meant to convey tranquility, letting listeners absorb information within a steady tone.
Heartwarming Sisterheartwarming_femaleTonghe in-houseFemalezh-CN5 credits/1K charsThe most pronounced high-frequency air of the sibling voices, far thinner and brighter in feel than the rest, and among the brightest overall. A clean timbre paired with a quick pace. Suited to content that needs a clear, transparent quality, such as beauty product detail walkthroughs and light science explainers, giving information more cut-through.
Kind Voicekind_femaleTonghe in-houseFemalezh-CN5 credits/1K charsThe most pronounced loudness variation among the sibling voices, with clear dynamics, and the fastest pace of the nine. A brightish, pure timbre free of grit. Suited to scenarios that need efficient delivery with emotional movement, such as news flashes and plot recaps, grabbing attention quickly while staying lively.
Energetic Female(internal members only)energetic_femaleTonghe in-houseFemalezh-CN5 credits/1K charsRich, natural breath pauses, each one carrying a sense of breathing, making it more relaxed and fluent than its sibling voices; a pure, grit-free timbre with neutral brightness that fits many scenarios. Suited to content that needs a natural breathing rhythm, such as relationship radio monologues and read-along children's stories, letting listeners feel a real spoken cadence.
Sweet Girl(internal members only)sweet_femaleTonghe in-houseFemalezh-CN5 credits/1K charsWide intonation swings and moderate breath pauses make this the most expressive, most breath-rich female voice of the nine siblings. Very high and bright, neutral clarity, quick pace. Suited to content that needs emotional tension and natural breathing, such as character voices in children's stories and relationship podcast narration, adding vividness and layers to the delivery.
Microsoft Azure (12) · 13 credits/1K chars
WanLung(experimental)azure_zh-HK-WanLungNeuralMicrosoft AzureMalezh-HK13 credits/1K charsA native Cantonese male voice, very dark in timbre and lowish in pitch, with flat intonation and a moderate pace. Narrates with the steady, storytelling feel of an old Hong Kong cha chaan teng, articulate and grounded. Suited to Hong Kong / Macau / Greater Bay Area commentary, classic Hong Kong film scene breakdowns and Cantonese roast-meat cooking tutorials.
Andrew Multilingual(experimental)azure_en-US-AndrewMultilingualNeuralMicrosoft AzureMaleen-US13 credits/1K charsAn English male voice with a darkish timbre and flat intonation, close to the feel of a real podcaster. Light natural breaths and linking in the flow; steady, restrained delivery, like a host sharing views from a late-night study. Suited to long-form English voice-over on in-depth content; easy on the ear over extended listening.
Yunyang(experimental)azure_zh-CN-YunyangNeuralMicrosoft AzureMalezh-CN13 credits/1K charsA male voice with a noticeably husky, breathy quality, lowish pitch, fairly wide intonation, quick pace and moderate pauses. Lands logical stress precisely on key words, as crisp as a senior industry analyst breaking down data, yet can ease off for casual news sharing. Suited to professional explainers and informal news reads.
Yunjian(experimental)azure_zh-CN-YunjianNeuralMicrosoft AzureMalezh-CN13 credits/1K charsA lowish male voice with a noticeably husky, breathy quality; moderate intonation, pauses and pace. Has a native documentary-narration feel: steady, never upstaging the picture, with sentence endings that settle naturally. Easy to follow over long texts and adapts to a film's shifts from calm passages to climaxes.
Yunxi (Sichuan)(experimental)azure_zh-CN-sichuan-YunxiNeuralMicrosoft AzureMalezh-CN · Sichuanese13 credits/1K charsA native Sichuan-Chongqing dialect male voice: medium pitch, neutral brightness and clarity, moderate intonation, generous pauses, quick pace. Carries the street-teahouse buzz of Sichuan, like a local gourmet who knows every back alley, vivid when talking hotpot spice levels or teahouse storytelling. Suited to fast-paced regional content.
Yunxi(experimental)azure_zh-CN-YunxiNeuralMicrosoft AzureMalezh-CN13 credits/1K charsA young male voice with generous pauses: medium pitch, neutral brightness and clarity, quick pace, moderate intonation. Like a friend who loves to share, brisk yet breathable when recounting travels, and able to hold a clear, light-science explainer when the style shifts.
Aria(experimental)azure_en-US-AriaNeuralMicrosoft AzureFemaleen-US13 credits/1K charsFlat intonation, medium pitch, neutral brightness and clarity. Narrates like a rigorous academic researcher: logical on global tech developments, precise on corporate product white papers, and steady without stiffness on lighter international culture news. Handles abbreviations and numbers in long scripts without stumbling. Suited to English narration across many scenarios.
Xiaohan(experimental)azure_zh-CN-XiaohanNeuralMicrosoft AzureFemalezh-CN13 credits/1K charsA bright, pure female voice free of grit: medium pitch, moderate intonation, pauses and pace. Narrates like soft talk by a window on a spring afternoon, gentle and composed with no forced sweetness. Suited to conveying the warmth of human-interest content; comfortable over long listening.
Xiaoxiao 2 HD Flash(experimental)azure_zh-CN-Xiaoxiao2:DragonHDFlashLatestNeuralMicrosoft AzureFemalezh-CN13 credits/1K charsWide intonation swings are this female voice's defining trait: medium pitch, neutral brightness and clarity, moderate pace, few pauses. Narrates like an excited messenger darting through the woods, emotional tension at full stretch, bringing flat content to life. Suited to scenarios that need to grab attention fast.
Xiaoxiao(experimental)azure_zh-CN-XiaoxiaoNeuralMicrosoft AzureFemalezh-CN13 credits/1K charsA highish female voice with a neutral timbre and clean delivery; moderate intonation, pauses and pace. Orderly and precise, with accurate stress placement and clear phrasing, like a news anchor seated before the camera in a live studio. Suited to formal news and official releases, and reliable across general narration.
Xiaozhen(experimental)azure_zh-CN-XiaozhenNeuralMicrosoft AzureFemalezh-CN13 credits/1K charsA highish, brightish female voice with crisp enunciation on a solid foundation; moderate intonation, pauses and pace. Delivers with brisk professionalism and no sugary affectation. Suited to steady delivery of professional content, staying grounded through long sentences and technical terms and lending credibility to what is taught.
Xiaoyi(experimental)azure_zh-CN-XiaoyiNeuralMicrosoft AzureFemalezh-CN13 credits/1K charsVery high and strikingly bright, with fairly wide intonation that never turns shrill; among Azure's Chinese female voices, distinctly youthful without sounding childish. Narrates like the girl next door bouncing over to share news, able to set a cheerful pace for food-spot visits or rein it in to explain the why behind a life hack. Suited to a range of light content.
Alibaba Cloud (14) · 21–42 credits/1K chars
Uncle Longali_longlaobo_v3Alibaba CloudMalezh-CN21 credits/1K charsA very low male voice with a dark timbre, neutral clarity, moderate intonation and pauses, and a slow pace. Carries the weight of lived years, like an elder recounting the past from an old rattan chair. Suited to period-memory content, where the sense of time in the voice makes the narrative feel authentic.
Storyteller Xiuali_longxiu_v3Alibaba CloudMalezh-CN21 credits/1K charsA male voice with a built-in storyteller's flair: lowish pitch, neutral timbre, slight rasp, quick pace with generous pauses and moderate intonation. Like a teahouse raconteur fanning himself between beats, skilled at planting hooks, building suspense and landing punchlines. Suited to film commentary, history storytelling and anything that needs to grab attention.
Easygoing Yichenali_longyichen_v3Alibaba CloudMalezh-CN21 credits/1K charsA young male voice with a noticeably husky, breathy quality; medium pitch, darkish timbre, fairly wide intonation, moderate pauses and pace. Delivers with an easygoing swagger, as casual as a sun-worn leather jacket, and stays grounded and untiring over long texts. Suited to commentary that needs youthful energy while carrying dense content.
Casual Anyangali_longanyangAlibaba CloudMalezh-CN21 credits/1K charsAn instruction-controllable male voice: medium pitch, neutral brightness, noticeably husky and breathy, fairly wide intonation, moderate pauses and pace. Delivers with a casual ease, like telling anecdotes among friends. Suited to scenarios where the mood needs flexible steering, switching between different expressive states.
Buddy Longali_longlaotie_v3Alibaba CloudMalezh-CN · Northeastern21 credits/1K charsA male voice with a native Northeastern dialect flavor: medium pitch, neutral brightness and clarity, moderate intonation and pace, generous pauses. Like an old neighbor squatting at the alley mouth for a chat, with a comic tone baked in. Suited to Northeastern street-life stories and snow-and-ice tourist anecdotes; dialect jokes land naturally when riffing.
Scholar Nanali_longnan_v3Alibaba CloudMalezh-CN21 credits/1K charsA medium-paced male voice with generous pauses: medium pitch, brightish timbre, neutral clarity, moderate intonation. Narrates like a young scholar at his desk unpacking complex ideas, logical without being dull, keeping listeners with him through long stretches of reasoning. Suited to making professional content plain and accessible.
Gentle Yuanali_longyuan_v3Alibaba CloudFemalezh-CN21 credits/1K charsA female voice whose brightish timbre is wrapped in a gentleness that comes with years; generous pauses, medium pitch, slow pace, moderate intonation like soft talk by an afternoon window. Suited to the fine emotions of human-interest stories and reflections on life; comfortable over long texts.
Bella 3.0ali_loongbella_v3Alibaba CloudFemalezh-CN21 credits/1K charsFairly wide intonation, medium pitch, neutral brightness and clarity, moderate pace and pauses. Enunciates every syllable cleanly, like an articulate professional breaking down a proposal with precision. Suited to professional narration of information-dense content.
Cheerful Anhuan (V3 Dialects)ali_longanhuan_v3Alibaba CloudFemalezh-CN21 credits/1K charsA female voice that switches among 9 dialects: highish pitch, neutral brightness and clarity, moderate intonation and pauses, quick pace. Brings the liveliness of regional context to narration, as natural and fitting as neighbors chatting. Suited to narrating and performing content across multiple regional themes.
Lead Reader Miaoali_longmiao_v3Alibaba CloudFemalezh-CN21 credits/1K charsA female voice with wide intonation swings: highish pitch, brightish timbre, neutral clarity, slow pace, generous pauses. Narrates with marked rise and fall, like a lead reader holding a baton, breaking complex content into rhythmic passages. Suited to content that needs an ear-catching cadence, with less of a machine-read feel.
Cheerful Anhuanali_longanhuanAlibaba CloudFemalezh-CN21 credits/1K charsA female voice with wide intonation swings, highish pitch, brightish timbre and neutral clarity. Narrates like a bubbly girl bouncing over to share the latest news. Suited to plot recaps, science explainers and match commentary; a change of instruction covers many genres, including food and lifestyle travel narration.
Cantonese Jiayiali_longjiayi_v3Alibaba CloudFemaleyue-HK21 credits/1K charsA very dark yet pure, grit-free Cantonese female voice, paired with highish pitch, flat intonation and a slow pace for an intellectual, trustworthy narrative feel. Like a thoughtful Cantonese speaker sharing by a late-night window. Suited to composed delivery of cultural content and regional news.
Anchor Jingali_longjing_v2Alibaba CloudFemalezh-CN42 credits/1K charsA slightly raspy, neutral timbre: medium pitch, moderate intonation and pace, few pauses. Carries a traditional air of authority, like a veteran anchor seated in the studio, delivering information with crisp, well-rounded diction. Suited to content that needs composure and credibility.
Narrator Baizhiali_longbaizhiAlibaba CloudFemalezh-CN42 credits/1K charsAn officially certified narration female voice: highish pitch, neutral brightness, clean delivery, moderate intonation, pauses and pace. Narrates with unhurried intelligence, like unpacking complex knowledge in a quiet study. Suited to professional content that needs credibility.
Volcengine (20) · 34–50 credits/1K chars
Late-Night Podcaster 2.0volc_zh_male_shenyeboke_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA very low male voice, dark in timbre with neutral clarity; moderate intonation, pauses and pace. Sounds like a host leaning into a radio mic late at night, relaxed and magnetic. Suited to nuanced personal essays, atmospheric city-nightscape travel footage, or setting the mood for suspense stories, with an unforced intimacy.
Elder Qingcang 2.0volc_zh_male_qingcang_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA very low, very dark male voice with a slight rasp that carries the weight of years; moderate intonation, slow pace, measured pauses. Narrates like an old scholar by the fire, lending historical gravity to tales of rising and falling dynasties. Comfortable over long texts, suited to deeply immersive content.
Haoran 2.0volc_zh_male_dongfanghaoran_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA very low, very dark male voice whose slight rasp holds steady strength; moderate intonation, slow pace, measured pauses. Like an engineer atop a dam recounting how it was built: uplifting without being rousing. Suited to grand narratives that need an upright, expansive feel.
Magnetic Narrator 2.0volc_zh_male_cixingjieshuonan_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA male voice with wide intonation swings, lowish pitch, dark timbre, a slight rasp, slow pace and generous pauses. Narrates like a fireside storyteller, painting pictures as he goes. Suited to content that needs emotional tension and rhythmic breathing room, drawing listeners into the unfolding plot or argument.
Yunzhou 2.0volc_zh_male_m191_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA male voice that switches among 8 dialects: lowish pitch, neutral timbre, slight rasp, moderate intonation and pace, few pauses. Sounds like a local sipping tea at the corner teahouse and sharing regional lore. Suited to cross-province dialect comparisons and regional food origin stories; keeping one voice identity across accents gives a series a consistent brand feel.
Suspense Narrator 2.0volc_zh_male_xuanyijieshuo_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA lowish, dark male voice with flattish intonation and a built-in sense that something is about to happen. Narrates like a hunter watching from the shadows, placing stress precisely on key plot points while moderate pauses let the tension build. Suited to suspense and thriller film commentary, and capable of long-form audiobook reading.
Casual Xiaoming 2.0volc_zh_male_jieshuoxiaoming_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsA quick-paced male voice with flat intonation and a slightly raspy, neutral timbre, like a friend your own age sharing what's new, relaxed and unpretentious. Suited to walk-and-talk narration in travel vlogs, fast-paced tech unboxings, or campus daily-life sharing, giving content a natural, eye-level warmth.
Vintage Dub Narrator 2.0volc_zh_male_yizhipiannan_uranus_bigttsVolcengineMalezh-CN34 credits/1K charsDefined by its wide intonation swings, paired with a slightly raspy voice and neutral brightness for a distinctive narrative cadence. Sounds like the voice-over in a vintage dubbed film: exaggerated phrasing and a slow pace collide into retro charm. Recreates the period feel of last century's cinema, or plays everyday trivia dead straight for comic contrast.
Margaretvolc_en_female_authoritative-informative_uranus_bigttsVolcengineFemaleen-US34 credits/1K charsA rare low-register female voice: medium pitch, neutral brightness and clarity, flattish intonation, few pauses. Her delivery is steady and dependable, like a guide tracing the story of an artifact in a quiet gallery, or a late-night radio voice explaining the cosmos, with built-in authority and substance.
Kenvolc_ja_male_bv524_uranus_bigttsVolcengineMaleja-JP34 credits/1K charsA Japanese male voice with flat intonation: medium pitch, neutral brightness and clarity, moderate pauses. Narrates like a composed travel guide, even-flowing and never erratic, good at conveying information clearly. Suited to Japanese culture and travel commentary, and to anime background explainers; dependable and never upstaging the content.
Yunzhou 2.0 (Shaanxi)volc_zh_male_m191_uranus_bigtts__shaanxiVolcengineMalezh-CN · Shaanxi34 credits/1K charsOne voice identity across 8 dialects: medium pitch, neutral brightness and clarity, moderate intonation, slow pace, few pauses. Narrates like a local guide fluent in several regional dialects. Suited to cross-province travel commentary and dialect culture explainers, letting audiences hear the same narrator switch accents naturally.
Yunzhou 2.0 (Northeastern)volc_zh_male_m191_uranus_bigtts__dongbeiVolcengineMalezh-CN · Northeastern34 credits/1K charsA single voice identity covering 8 dialects: medium pitch, dark and clean timbre, flat intonation, moderate pauses and pace. Narrates like a composed elder at a fireside chat, keeping a consistent texture across dialects. Suited to cross-province cultural exploration; Shanghainese is its distinctive dialect strength.
Brisk Sisi 2.0volc_zh_female_shuangkuaisisi_uranus_bigttsVolcengineFemalezh-CN34 credits/1K charsCrisp, no-dawdling delivery: medium pitch, neutral brightness and clarity, moderate intonation, pauses and pace. Like a city girl with a light step sharing her day, lively without being cloying and free of any put-on distance. Well suited to narrating lifestyle content.
Gentle Xiaoya 2.0volc_zh_female_wenrouxiaoya_uranus_bigttsVolcengineFemalezh-CN34 credits/1K charsGenerous pauses leave breath-like gaps in the narration; medium pitch, neutral and clean timbre, moderate intonation, slow pace. Gentle and restrained, like a flagstone lane in an old town at dawn. Suited to slowly unfolding human-interest scenes, such as an ancient town waking at first light or stories of old objects in old alleys, with an unhurried sense of company.
Yunzhou 2.0 (Sichuan)volc_zh_male_m191_uranus_bigtts__sichuanVolcengineMalezh-CN · Sichuanese34 credits/1K charsOne consistent voice across 8 dialects: medium pitch, neutral brightness and clarity, flattish intonation, moderate pauses and pace. Narrates like a local guide fluent in several dialects, even-toned and unshowy. Suited to cross-regional content, giving audiences from different dialect areas a sense of familiarity.
Intellectual Female 2.0volc_zh_female_zhixingnv_uranus_bigttsVolcengineFemalezh-CN34 credits/1K charsDefined by a narration rhythm with very few pauses: medium pitch, neutral brightness and clarity, moderate intonation, slow pace. Clear diction with no surplus emotion, like a quiet display case for knowledge that lets the information itself take focus. Suited to objective content where the voice should never get in the way.
Vivi (Shaanxi)volc_zh_female_vv_uranus_bigtts__shaanxiVolcengineFemalezh-CN · Shaanxi34 credits/1K charsA very high female voice with neutral brightness and clarity, fairly wide intonation, slow pace and very few pauses. Like a Shaanxi auntie on a bamboo chair at the alley mouth telling stories, vivid and spirited, making old tales from beneath the city wall taste of life. Suited to life stories with a regional flavor.
Vivi (Northeastern)volc_zh_female_vv_uranus_bigtts__dongbeiVolcengineFemalezh-CN · Northeastern34 credits/1K charsA pure, grit-free, very high female voice with moderate intonation, pauses and pace. Narrates like a girl chatting in the sun in a Northeastern courtyard, clean yet carrying the dialect's characteristic warmth. Suited to down-to-earth everyday content, and capable in scenarios that call for clear expression.
Vivi (Sichuan)volc_zh_female_vv_uranus_bigtts__sichuanVolcengineFemalezh-CN · Sichuanese34 credits/1K charsA Sichuan-Chongqing female voice with very few pauses: very high pitch, neutral and clean timbre, flattish intonation, slow pace. Like a local girl spinning slow yarns in an old corner teahouse, steady without dragging. Suited to working the everyday flavor of dialect into content.
Harmony (Beijing Banter)volc_zh_male_jingqiangkanye_moon_bigttsVolcengineMalezh-CN50 credits/1K charsA medium-pitched, darkish male voice with flat intonation and the laid-back feel of hutong banter, like old Beijing buddies shooting the breeze, with a wry, slightly dark take hidden in the wisecracks. Suited to unpacking social phenomena or exposing consumer traps in a 'let's talk this through' tone that closes the distance.

This table is generated from the server-side voice catalog, not maintained by hand. For the full field set (persona, tags, suited subjects, speed range) see Voice Catalog & Search. The "Source (engine)" column mirrors the engine field of the voice catalog endpoint (Tonghe in-house = gpt_sovits, Alibaba Cloud = aliyun, Volcengine = volcengine, Microsoft Azure = azure) and can be used directly as that endpoint's engine filter value; the price per 1,000 characters differs by source, matching the billing tiers of "Voice Clone TTS" on the pricing page. Rows are grouped by source, groups ordered by their lowest price and rows within a group by price ascending. "Demo" plays a sample clip; every voice reads the same line so they can be compared directly. Voices marked "internal members only" are available to Gitruck Cloud internal members; other accounts requesting them receive a parameter error explaining why.

Billing

Billed by the character count of the input text, in units of 1,000 characters.

  • Billable units = text character count ÷ 1000 (fractional units are preserved)
  • Billing depends only on the text you submit, not on the length of the synthesized audio — slowing the speed makes the audio longer but does not change the charge
  • The final charge is rounded up to a whole credit; any non-empty text costs at least 1 credit

The unit price depends on the voice's engine and tier (5–50 credits per 1,000 characters); see the credits_per_kchar field returned by the voice list endpoint, which matches the "Voice Clone TTS" tiers on the pricing page.

How characters are counted

RuleDetail
Counting basisUnicode code points — one Chinese, Japanese, or Korean character counts as 1; Latin counts per letter and numbers per digit
Leading/trailing whitespaceNot counted (text is trimmed before validation)
Inner spaces, newlines, punctuationCounted as 1 each

For example, 1000 characters = 1 unit; synthesized with a voice priced at 5 credits per 1,000 characters, that costs 5 credits.

⚠️ The billing unit changed from "minutes" to "1,000 characters" in August 2026. The earlier wording — "billed by synthesized duration, with billed minutes derived at 240 chars/minute" — is obsolete. That conversion was a pseudo-unit and has been removed: a capability billed per character should state its unit in characters.

During the transition the voice list endpoint returns both credits_per_kchar (current) and credits_per_minute (deprecated, kept only because older docs told users to read it). credits_per_minute will be removed after the announcement period. New integrations should read credits_per_kchar only.

Example Request

curl -X POST https://api.ai-mcn.tv:10000/task/audio_tts_clone \
  -H "Authorization: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Hello, welcome to this episode.",
    "speaker": "narrator",
    "output_format": "wav",
    "speed": 1.0
  }'

Success Response

{
  "code": 200,
  "msg": "success",
  "data": {
    "task_id": "537489015178247",
    "task_type": "audio_tts_clone",
    "status": "queued"
  }
}

Query Task Result

Basics

ItemValue
MethodGET
Path/task/audio_tts_clone/{task_id}
AuthAuthorization header (pass the API Key directly)

Response (output_result)

FieldTypeDescription
file_idstringSynthesized audio file ID
download_urlstringAudio download path
speakerstringVoice code used
voice_idstringSame as speaker (aligned with the voice list endpoint's field name)
enginestringSynthesis engine
sample_rateintegerAudio sample rate (Hz)
duration_msintegerActual audio length in milliseconds. Unrelated to billing — billing depends only on the input text's character count
billed_charsintegerCharacter count reported by the upstream engine. Cloud voices only (self-trained gpt_sovits voices do not return this field). ⚠️ It is an upstream usage record, not your billing basis: engines count differently (Volcengine reports upstream usage.text_words, for example), while your charge always follows the rules in "How characters are counted" above
segmentsarrayPer-sentence timing [{index, text, start_ms, end_ms}]: where each sentence starts and ends in the audio, ready for subtitle alignment and cut points. end_ms includes the sentence-final pause; the timeline is contiguous with no gaps. Always present for cloud voices; for self-trained voices the granularity follows the text_split_method request parameter (see the request table above; the cut1 default groups up to 4 sentences per segment) — pass cut5 for one sentence per segment
subtitle_file_idstringSubtitle file (.srt) ID. Present only when subtitle_format was requested; empty string if generation failed, with the reason in errors.subtitle
subtitle_file_download_urlstringSubtitle file download path
errorsobjectPresent only when a bonus artifact was degraded. Subtitle failures are recorded under errors.subtitle — the task is still completed and the audio is unaffected
cache_hitbooleanPresent (and true) only when the synthesis cache was hit — the audio is reused from the previous run

Success Response

{
  "code": 200,
  "msg": "success",
  "data": {
    "task_id": "537489015178247",
    "status": "completed",
    "progress": 100,
    "output_result": {
      "file_id": "537489015178248",
      "download_url": "/download/a1/output_tts.wav",
      "speaker": "narrator",
      "voice_id": "narrator",
      "engine": "gpt_sovits",
      "sample_rate": 32000,
      "duration_ms": 5240,
      "billed_chars": 16,
      "segments": [
        { "index": 0, "text": "First sentence here.", "start_ms": 0, "end_ms": 2600 },
        { "index": 1, "text": "Second sentence here.", "start_ms": 2600, "end_ms": 5240 }
      ]
    },
    "create_time": "2026-06-21T08:00:00Z",
    "update_time": "2026-06-21T08:00:12Z"
  }
}

Error Codes

CodeHTTPDescriptionResolution
6013400Missing required parameter (text / speaker)Provide the parameter
6016400Invalid business parameter (unavailable speaker, empty or overlong text, speed out of range, invalid subtitle_format, invalid canvas or canvas sent without subtitle_format, fragment_interval out of range, fragment_interval passed with a cloud voice, etc.)Fix per the parameter spec
6502401Authentication failedCheck the Authorization header
6201402Insufficient quotaTop up in the dashboard
6202402Insufficient balanceTop up in the dashboard

Limits

⚠️ Behavior change (2026-09-13): As of 2026-09-13, requests with subtitle_format split overly long sentences into multiple subtitle lines for the canvas; when canvas is omitted the portrait default [1080, 1920] is used, so subtitle lines are shorter than the previous one-cue-per-sentence output. The audio, segments, and each sentence's start and end timings are unchanged. For landscape videos, pass canvas: [1920, 1080] explicitly.

⚠️ Behavior change (2026-08-22): As of 2026-08-22, the bonus .srt subtitle from subtitle_format strips Chinese and English commas and periods from its text by default (strip_punctuation defaults to true), so identical requests produce different subtitle text than before the upgrade; timecodes, line counts, the audio, segments, and all other output fields are unchanged. To keep the previous behavior, pass strip_punctuation: false explicitly.

  • Up to 5000 characters per request. Long text is split into sentences and synthesized sentence by sentence server-side, so you do not need to split it — but longer means slower: the slowest engine runs at roughly 0.11 s per character, so 5000 characters takes about 9 minutes.
  • Long text is split into sentences server-side, synthesized sentence by sentence and concatenated; no need to split it yourself. Cloud voices synthesize sentences in parallel — long scripts take roughly a third of the serial time (Alibaba voices remain serial for now).
  • Resubmitting with identical parameters (text, voice, speed, format) hits the synthesis cache and returns the previous audio (same file_id) almost instantly; billing is unchanged. For a fresh take (synthesis is non-deterministic — every re-synthesis is a new performance), pass "refresh": true.
  • Subtitles (subtitle_format) are free: they are generated from the per-sentence timeline this run already produced, so the timings match the audio exactly (millisecond precision, no rounding). Subtitles break where segments break first (for self-trained voices, pass text_split_method: "cut5" to break at every sentence end; cloud voices always produce one sentence per segment), then overly long sentences are split into lines for the canvas.
  • Subtitles are a bonus artifact: if generation fails (e.g. the per-sentence timeline is unusable for a particular self-trained run), the task still completes and the audio is returned as usual, with subtitle_file_id empty and the reason in errors.subtitle.
  • Sentence pauses are adjustable (fragment_interval): in-house voices let you tighten the gap between sentences. Measured reference: in a 203-second narration, roughly a quarter of the runtime is inter-sentence silence; setting the pause to 0.2 seconds brings the same script down to 171 seconds. Omit it and the voice's own tuned preset is used — the output is byte-for-byte identical to what it was before this parameter shipped.
  • Cloud voices do not support adjusting sentence pauses: passing fragment_interval returns a parameter error outright (no task created, nothing billed) rather than being silently ignored — you will not be handed audio that "looks unchanged" and left guessing. For a tighter rhythm, switch to a Tonghe in-house voice.
  • Only authorized, quality-approved voices are available (see "Available Voices").
  • Voices marked "internal members only" require Gitruck Cloud internal membership; other accounts requesting them receive a parameter error (no silent fallback to another voice).

🤝 Join the Tonghe New Media Network to unlock internal member benefits: network members (internal) get custom-scope full-library material search (video / image / audio, including concept and non-commercial materials, with a commercial-only filter) and exclusive internal voices. Apply at the Creator Network; once approved, an administrator will enable internal access for you.