# 1. upload an audio or video file by link
curl -X POST https://api.rask.ai/api/library/v1/media/link \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-d '{"link": "https://example.com/interview.mp3", "name": "interview"}'
# 2. create the project - speech recognition starts automatically
# src_lang is optional: leave it out and the language is detected
curl -X POST https://api.rask.ai/v2/projects \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-d "{\"video_id\": \"$MEDIA_ID\", \"dst_lang\": \"es-mx\"}"# Read the transcript: one object per segment
curl -s https://api.rask.ai/v2/projects/$ID/transcription -H "Authorization: Bearer $TOKEN" \
| jq '.segments[] | {speaker, start, end, text: .src.text}'以多部分表单数据形式发送音频或视频文件,或者提交来自 YouTube、Google Drive、S3、Vimeo 或任何直接网址的链接。在产生任何费用之前,您将获得媒体 ID 和文件元数据。
将媒体 ID 作为 video_id 传入,并指定目标语言。如果您知道源语言或说话人数,也可以一并添加。系统将立即开始识别。
一旦文字片段可用,即可在翻译后的媒体仍在处理时阅读文字记录。项目完成后,下载字幕和媒体文件。
# pip install git+ssh://[email protected]/braskai/rask-sdk.git@main
import asyncio
from rask_sdk import clients, enums, schemas
async def main():
client = clients.RaskSDKClient(client_id=CLIENT_ID, client_secret=CLIENT_SECRET)
media = await client.create_media_link(data=schemas.MediaCreateLink(link="https://example.com/interview.mp3"))
while media.status is enums.MediaStatus.PROCESSING:
await asyncio.sleep(5)
media = await client.get_media(media_id=media.id)
# src_lang omitted: the source language is detected automatically
job = await client.create_project(data=schemas.ProjectCreate(video_id=media.id, dst_lang="es-mx"))
while job.status is not enums.ProjectStatus.MERGING_DONE:
await asyncio.sleep(10)
job = await client.get_project(project_id=job.id)
transcript = await client.get_project_transcription(project_id=job.id)
for seg in transcript.segments:
print(seg.start, seg.end, seg.speaker, seg.src.text)
asyncio.run(main())import time, requests
AUTH = "https://rask-prod.auth.us-east-2.amazoncognito.com/oauth2/token"
API = "https://api.rask.ai"
token = requests.post(AUTH, auth=(CLIENT_ID, CLIENT_SECRET),
data={"grant_type": "client_credentials"}).json()["access_token"]
h = {"Authorization": f"Bearer {token}"}
with open("interview.mp3", "rb") as f:
media = requests.post(f"{API}/api/library/v1/media", headers=h,
params={"kind": "audio"}, files={"data": f}).json()
while media["status"] == "processing":
time.sleep(5)
media = requests.get(f"{API}/api/library/v1/media/{media['id']}", headers=h).json()
pid = requests.post(f"{API}/v2/projects", headers=h, json={
"video_id": media["id"], "dst_lang": "es-mx", "num_speakers": 2}).json()["id"]
while requests.get(f"{API}/v2/projects/{pid}", headers=h).json()["status"] != "merging_done":
time.sleep(10)
# write the source transcript as an .srt file
segments = requests.get(f"{API}/v2/projects/{pid}/transcription", headers=h).json()["segments"]
with open("interview_en.srt", "w") as out:
for i, s in enumerate(segments, 1):
out.write(f"{i}\n{s['start']} --> {s['end']}\n{s['speaker']}: {s['src']['text']}\n\n")// no dependencies, Node 18+ global fetch
const API = 'https://api.rask.ai';
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
const auth = await fetch('https://rask-prod.auth.us-east-2.amazoncognito.com/oauth2/token', {
method: 'POST',
headers: { Authorization: 'Basic ' + btoa(`${CLIENT_ID}:${CLIENT_SECRET}`) },
body: new URLSearchParams({ grant_type: 'client_credentials' }),
}).then((r) => r.json());
const h = { Authorization: `Bearer ${auth.access_token}`, 'Content-Type': 'application/json' };
const call = (method, path, body) => fetch(API + path, { method, headers: h, body: body && JSON.stringify(body) }).then((r) => r.json());
let media = await call('POST', '/api/library/v1/media/link', { link: 'https://example.com/webinar.mp4' });
while (media.status === 'processing') { await sleep(5000); media = await call('GET', `/api/library/v1/media/${media.id}`); }
let p = await call('POST', '/v2/projects', { video_id: media.id, src_lang: 'en', dst_lang: 'de-de' });
while (p.status !== 'merging_done') { await sleep(10000); p = await call('GET', `/v2/projects/${p.id}`); }
const { segments } = await call('GET', `/v2/projects/${p.id}/transcription`);
segments.forEach((s) => console.log(`[${s.start}] ${s.speaker}: ${s.src.text}`));
console.log(p.translation_vtt_path); // German subtitles for your player# 1. token (valid 1 hour - cache and reuse it)
TOKEN=$(curl -s -X POST https://rask-prod.auth.us-east-2.amazoncognito.com/oauth2/token \
-u "$CLIENT_ID:$CLIENT_SECRET" -d "grant_type=client_credentials" | jq -r .access_token)
# 2. upload a local audio file
MEDIA_ID=$(curl -s -X POST "https://api.rask.ai/api/library/v1/media?kind=audio" \
-H "Authorization: Bearer $TOKEN" -F "data=@podcast_episode.mp3" | jq -r .id)
# 3. create the project once the media status is ready
ID=$(curl -s -X POST https://api.rask.ai/v2/projects \
-H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \
-d "{\"video_id\": \"$MEDIA_ID\", \"dst_lang\": \"fr-fr\"}" | jq -r .id)
# 4. when status is merging_done, read the transcript with speaker labels
curl -s https://api.rask.ai/v2/projects/$ID/transcription -H "Authorization: Bearer $TOKEN" \
| jq -r '.segments[] | "\(.start) \(.speaker): \(.src.text)"'<?php
use GuzzleHttp\Client;
$http = new Client(['base_uri' => 'https://api.rask.ai']);
$json = fn($r) => json_decode($r->getBody(), true);
$auth = $json((new Client)->post('https://rask-prod.auth.us-east-2.amazoncognito.com/oauth2/token',
['auth' => [$clientId, $clientSecret], 'form_params' => ['grant_type' => 'client_credentials']]));
$h = ['Authorization' => 'Bearer ' . $auth['access_token']];
$media = $json($http->post('/api/library/v1/media/link', ['headers' => $h, 'json' => [
'link' => 'https://example.com/interview.mp3']]));
while ($media['status'] === 'processing') {
sleep(5);
$media = $json($http->get("/api/library/v1/media/{$media['id']}", ['headers' => $h]));
}
$p = $json($http->post('/v2/projects', ['headers' => $h, 'json' => [
'video_id' => $media['id'], 'dst_lang' => 'es-mx']]));
while ($p['status'] !== 'merging_done') {
sleep(10);
$p = $json($http->get("/v2/projects/{$p['id']}", ['headers' => $h]));
}
$t = $json($http->get("/v2/projects/{$p['id']}/transcription", ['headers' => $h]));
foreach ($t['segments'] as $s) {
echo $s['start'], ' ', $s['speaker'], ': ', $s['src']['text'], PHP_EOL;
}{"segments": [
{"speaker": "SPEAKER_00", "start": "00:00:00,320", "end": "00:00:07,316", "status": "done",
"src": {"text": "Thanks for joining us. Let's start with the new release.", "lang": "en"},
"dst": {"text": "Gracias por acompañarnos. Empecemos con la nueva versión.", "lang": "es-mx"}},
{"speaker": "SPEAKER_01", "start": "00:00:07,640", "end": "00:00:11,900", "status": "done",
"src": {"text": "Sure. The biggest change is the reporting view.", "lang": "en"},
"dst": {"text": "Claro. El cambio más grande es la vista de reportes.", "lang": "es-mx"}}
]}

es-mx 和 es-es 类似项目。项目记录 glossary_version,因此后续的修改绝不会悄悄改变已完成的工作。提供。语音识别是每个Rask项目的第一步。只需上传音频或视频、创建一个项目,即可通过 GET /v2/projects/{id}/transcription 读取带有发言人标签和时间戳的分段文字记录。同一个项目还能翻译文字记录,并返回字幕和配音音频。
该API支持75种源语言。将src_lang留空即可自动检测语言,或者传入如en或de等双字母代码。文字记录可被翻译成135种以上的语言和地区选项。
可以。您可以上传MP3、WAV、FLAC或M4A格式的音频文件(如播客、采访和录音通话),项目会像处理视频一样对其进行转写。
支持。系统会自动检测不同的发言人,每个分段都会带有SPEAKER_XX格式的发言人标签。如果您知道人数,可以传入num_speakers,也可以通过API更正任何分段的发言人。
不会。时间戳是分段级别的:每个分段都有一个以HH:MM:SS,mmm格式表示的开始时间和结束时间。这就是字幕所使用的计时方式。如果您需要每个词的时间戳,请选择专门的语音转文字API。
不支持。Rask转写的是完整的、预先录制的音频和视频。对于需要在一边说话一边出文字的实时字幕、语音代理、对话式AI和呼叫中心,流式语音转文字API是更好的选择。
准确度取决于音频本身:麦克风、口音、重叠语音和背景噪音都会产生影响。您可以在自己的录音样本上测试API,并在发布或翻译之前通过API更正任何分段。
识别过程不使用自定义词汇表。您可以通过分段端点更正文字记录中的特定词汇。翻译文字记录时,词汇表可确保产品名称、专有名词和专业术语保持一致。
完成的项目包含目标语言的SRT和VTT格式字幕文件。源语言文字记录则以带有开始和结束时间的JSON分段形式提供,只需几行代码即可将其转换为SRT。
可以。在支持文字记录导入的套餐中,您可以在创建项目时提供现有的源文字记录、经批准的目标语言翻译,或者两者的SRT文件及定时文本分段。Rask可以翻译您的源脚本,或者使用您批准的翻译进行配音。
项目按音频或视频的时长计费(按分钟向上取整),并从 Rask 应用的同一分钟额度中扣除。价格包含文字转录、翻译、配音和字幕。在符合条件的标准套餐中,额外购买时长为每分钟 3 美元。企业版定价则根据您的具体协议定制。如果您只需要文字记录,专用的语音转文字 API 费用会更低。
您可以在 Rask 应用中通过免费试用来测试您自己的文件的文字转录和翻译功能,无需绑定信用卡。创作者专业版、企业版和企业专属套餐均提供 API 访问权限,具体功能取决于您选择的套餐。
API权限适用于创作者专业版、商业版和企业版套餐,具体功能由您的套餐决定。您可以在应用中生成客户端ID和密钥,然后立即开始调用。企业条款、大宗优惠价格以及自定义语言覆盖范围请联系我们的团队咨询。