OpenAI API参考文档 | OpenAI开发文档|OpenAI中文官方文档|ChatGPT中文版|ChatGPT教程

Audio

Learn how to turn audio into text or text into audio.source

Related guide: Speech to text source

Create speech

post https://api.openai.com/v1/audio/speech

Generates audio from the input text.source

Request body

model

stringsource

Required

One of the available TTS models: tts-1 or tts-1-hdsource

input

stringsource

Required

The text to generate audio for. The maximum length is 4096 characters.source

voice

stringsource

Required

The voice to use when generating the audio. Supported voices are alloy, echo, fable, onyx, nova, and shimmer. Previews of the voices are available in the Text to speech guide.source

response_format

stringsource

Optional

Defaults to mp3

The format to audio in. Supported formats are mp3, opus, aac, flac, wav, and pcm.source

speed

numbersource

Optional

Defaults to 1

The speed of the generated audio. Select a value from 0.25 to 4.0. 1.0 is the default.source

Returns

The audio file content.source

Example request

1
2
3
4
5
6
7
8
9
curl https://api.openai.com/v1/audio/speech \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "The quick brown fox jumped over the lazy dog.",
    "voice": "alloy"
  }' \
  --output speech.mp3

1
2
3
4
5
6
7
8
9
10
from pathlib import Path
import openai

speech_file_path = Path(__file__).parent / "speech.mp3"
response = openai.audio.speech.create(
  model="tts-1",
  voice="alloy",
  input="The quick brown fox jumped over the lazy dog."
)
response.stream_to_file(speech_file_path)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
import fs from "fs";
import path from "path";
import OpenAI from "openai";

const openai = new OpenAI();

const speechFile = path.resolve("./speech.mp3");

async function main() {
  const mp3 = await openai.audio.speech.create({
    model: "tts-1",
    voice: "alloy",
    input: "Today is a wonderful day to build something people love!",
  });
  console.log(speechFile);
  const buffer = Buffer.from(await mp3.arrayBuffer());
  await fs.promises.writeFile(speechFile, buffer);
}
main();

Create transcription

post https://api.openai.com/v1/audio/transcriptions

Transcribes audio into the input language.source

Request body

file

filesource

Required

The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.source

model

stringsource

Required

ID of the model to use. Only whisper-1 (which is powered by our open source Whisper V2 model) is currently available.source

language

stringsource

Optional

The language of the input audio. Supplying the input language in ISO-639-1 format will improve accuracy and latency.source

prompt

stringsource

Optional

An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.source

response_format

stringsource

Optional

Defaults to json

The format of the output, in one of these options: json, text, srt, verbose_json, or vtt.source

temperature

numbersource

Optional

Defaults to 0

The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.source

timestamp_granularities[]

arraysource

Optional

Defaults to segment

The timestamp granularities to populate for this transcription. response_format must be set verbose_json to use timestamp granularities. Either or both of these options are supported: word, or segment. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.source

Returns

The transcription object or a verbose transcription object.source

Example request

1
2
3
4
5
curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/audio.mp3" \
  -F model="whisper-1"

1
2
3
4
5
6
7
8
from openai import OpenAI
client = OpenAI()

audio_file = open("speech.mp3", "rb")
transcript = client.audio.transcriptions.create(
  model="whisper-1",
  file=audio_file
)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
import fs from "fs";
import OpenAI from "openai";

const openai = new OpenAI();

async function main() {
  const transcription = await openai.audio.transcriptions.create({
    file: fs.createReadStream("audio.mp3"),
    model: "whisper-1",
  });

  console.log(transcription.text);
}
main();

Response

1
2
3
{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
}

Create translation

post https://api.openai.com/v1/audio/translations

Translates audio into English.source

Request body

file

filesource

Required

The audio file object (not file name) translate, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.source

model

stringsource

Required

ID of the model to use. Only whisper-1 (which is powered by our open source Whisper V2 model) is currently available.source

prompt

stringsource

Optional

An optional text to guide the model's style or continue a previous audio segment. The prompt should be in English.source

response_format

stringsource

Optional

Defaults to json

The format of the output, in one of these options: json, text, srt, verbose_json, or vtt.source

temperature

numbersource

Optional

Defaults to 0

Returns

The translated text.source

Example request

1
2
3
4
5
curl https://api.openai.com/v1/audio/translations \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/file/german.m4a" \
  -F model="whisper-1"

1
2
3
4
5
6
7
8
from openai import OpenAI
client = OpenAI()

audio_file = open("speech.mp3", "rb")
transcript = client.audio.translations.create(
  model="whisper-1",
  file=audio_file
)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
import fs from "fs";
import OpenAI from "openai";

const openai = new OpenAI();

async function main() {
    const translation = await openai.audio.translations.create({
        file: fs.createReadStream("speech.mp3"),
        model: "whisper-1",
    });

    console.log(translation.text);
}
main();

Response

1
2
3
{
  "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
}

The transcription object (JSON)

Represents a transcription response returned by model, based on the provided input.source

text

stringsource

The transcribed text.source

OBJECT The transcription object (JSON)

1
2
3
{
  "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
}

The transcription object (Verbose JSON)

Represents a verbose json transcription response returned by model, based on the provided input.source

language

stringsource

The language of the input audio.source

duration

stringsource

The duration of the input audio.source

text

stringsource

The transcribed text.source

words

arraysource

Extracted words and their corresponding timestamps.source

segments

arraysource

Segments of the transcribed text and their corresponding details.source

OBJECT The transcription object (Verbose JSON)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
{
  "task": "transcribe",
  "language": "english",
  "duration": 8.470000267028809,
  "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
  "segments": [
    {
      "id": 0,
      "seek": 0,
      "start": 0.0,
      "end": 3.319999933242798,
      "text": " The beach was a popular spot on a hot summer day.",
      "tokens": [
        50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
      ],
      "temperature": 0.0,
      "avg_logprob": -0.2860786020755768,
      "compression_ratio": 1.2363636493682861,
      "no_speech_prob": 0.00985979475080967
    },
    ...
  ]
}