Audio Transcription & Speech Synthesis API

Overview

LaoZhang API provides powerful audio processing capabilities, including Speech-to-Text (STT) and Text-to-Speech (TTS). Using the unified OpenAI API format, you can easily implement meeting transcription, subtitle generation, voice assistants, audiobook creation and more. 🎙️ Intelligent Audio Processing
Support for multi-language audio transcription, HD voice synthesis, and real-time streaming - let AI truly “hear” and “speak” your content.

🌟 Key Features

🎯 Multiple Models: GPT-4o Transcribe, Whisper, TTS-1/HD and other professional audio models
🌍 Multi-language: Support for 50+ languages in audio transcription
🎤 High Quality: Standard and HD quality voice synthesis
🗣️ Multiple Voices: 6 different voice options available
⚡ Fast Response: High-performance processing with sub-second results
💰 Flexible Pricing: Pay per token or duration, cost-effective

📋 Supported Audio Models

Speech-to-Text (Transcription)

Model Name	Model ID	Billing	Features
GPT-4o Transcribe ⭐	`gpt-4o-transcribe`	Token	High accuracy, multi-language
GPT-4o Mini Transcribe	`gpt-4o-mini-transcribe`	Token	Fast and efficient, low cost
Whisper v1	`whisper-1`	Duration (seconds)	OpenAI Whisper model

Text-to-Speech (TTS)

Model Name	Model ID	Quality	Features
TTS-1 ⭐	`tts-1`	Standard	Fast generation, real-time apps
TTS-1 HD	`tts-1-hd`	HD Quality	Better audio, content creation

Available Voice Options

alloy - Neutral, clear and natural
echo - Male voice, steady and strong
fable - British accent, elegant
onyx - Deep male voice, news/broadcast
nova - Female voice, warm and friendly
shimmer - Soft female voice, narration

🎙️ Speech-to-Text

1. Basic Example - cURL

curl -X POST "https://api.yelinai.com/v1/audio/transcriptions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@audio.mp3" \
  -F "model=gpt-4o-transcribe"

Response Example:

{
  "text": "Hello, this is a test audio.",
  "usage": {
    "type": "tokens",
    "total_tokens": 32,
    "input_tokens": 23,
    "output_tokens": 9
  }
}

2. Python Example - Using OpenAI SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

# Method 1: Pass file directly
with open("audio.mp3", "rb") as audio_file:
    transcript = client.audio.transcriptions.create(
        model="gpt-4o-transcribe",
        file=audio_file
    )

print(transcript.text)

3. Specify Language and Response Format

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

with open("audio.mp3", "rb") as audio_file:
    transcript = client.audio.transcriptions.create(
        model="whisper-1",
        file=audio_file,
        language="en",  # Specify language: English
        response_format="json"  # Options: json, text, srt, vtt, verbose_json
    )

print(transcript.text)

4. Using Whisper Model (Duration-based Billing)

curl -X POST "https://api.yelinai.com/v1/audio/transcriptions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@audio.wav" \
  -F "model=whisper-1" \
  -F "language=en"

Response Example:

{
  "text": "Hello, this is a test audio.",
  "usage": {
    "type": "duration",
    "seconds": 3
  }
}

Supported Audio Formats

Supports the following audio formats (max file size 25 MB):

mp3 - MP3 audio file
mp4 - MP4 audio file
mpeg - MPEG audio file
mpga - MPEG audio file
m4a - M4A audio file
wav - WAV audio file
webm - WebM audio file

🗣️ Text-to-Speech

1. Basic Example - cURL

curl -X POST "https://api.yelinai.com/v1/audio/speech" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "Hello, welcome to LaoZhang API speech synthesis.",
    "voice": "alloy"
  }' \
  --output speech.mp3

2. Python Example - Generate Audio File

from openai import OpenAI
from pathlib import Path

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

response = client.audio.speech.create(
    model="tts-1",
    voice="nova",
    input="This is text content to be converted to speech."
)

# Save as MP3 file
response.stream_to_file("output.mp3")

3. Using HD Model

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

response = client.audio.speech.create(
    model="tts-1-hd",  # Use HD model
    voice="shimmer",
    input="Using the HD model provides better audio quality.",
    speed=1.0  # Speed: 0.25 to 4.0, default 1.0
)

response.stream_to_file("speech_hd.mp3")

4. Adjust Speech Speed

# Fast playback (1.5x speed)
response = client.audio.speech.create(
    model="tts-1",
    voice="onyx",
    input="This content will play at 1.5x speed.",
    speed=1.5
)

response.stream_to_file("speech_fast.mp3")

5. Real-time Streaming Output

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

response = client.audio.speech.create(
    model="tts-1",
    voice="alloy",
    input="Real-time streaming allows playback while generating for better UX."
)

# Stream audio data
response.stream_to_file("streaming_speech.mp3")

🎯 Common Use Cases

1. Meeting Transcription

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

# Transcribe meeting recording
with open("meeting.mp3", "rb") as audio_file:
    transcript = client.audio.transcriptions.create(
        model="gpt-4o-transcribe",
        file=audio_file,
        response_format="text"
    )

# Save as text file
with open("meeting_transcript.txt", "w", encoding="utf-8") as f:
    f.write(transcript.text)

2. Video Subtitle Generation

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

# Generate SRT subtitle file
with open("video_audio.mp3", "rb") as audio_file:
    transcript = client.audio.transcriptions.create(
        model="whisper-1",
        file=audio_file,
        response_format="srt"  # SRT subtitle format
    )

# Save subtitle file
with open("subtitles.srt", "w", encoding="utf-8") as f:
    f.write(transcript.text)

3. Multi-language Content Broadcasting

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

# Generate speech in multiple languages
texts = {
    "Chinese": "欢迎使用YeLIn AI",
    "English": "Welcome to LaoZhang API",
    "Japanese": "ようこそ"
}

for lang, text in texts.items():
    response = client.audio.speech.create(
        model="tts-1",
        voice="nova",
        input=text
    )
    response.stream_to_file(f"welcome_{lang}.mp3")

4. Audiobook Creation

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

# Convert long text to speech
with open("book_chapter.txt", "r", encoding="utf-8") as f:
    text = f.read()

# Process in segments (TTS has character limit)
max_chars = 4096
segments = [text[i:i+max_chars] for i in range(0, len(text), max_chars)]

for idx, segment in enumerate(segments):
    response = client.audio.speech.create(
        model="tts-1-hd",  # Use HD model
        voice="fable",  # Good for narration
        input=segment
    )
    response.stream_to_file(f"audiobook_part_{idx+1}.mp3")

💡 Best Practices

Speech-to-Text Optimization

Audio Quality:
- Sample rate ≥16 kHz recommended
- Lower background noise improves accuracy
- Clear voice recording works best
File Size:
- Single file ≤25 MB
- Split large files into segments
Language Specification:
- Specify language for better accuracy
- Supported codes: zh (Chinese), en (English), ja (Japanese), etc.
Response Format Selection:
- json: Default format with full information
- text: Plain text output
- srt/vtt: Subtitles with timestamps
- verbose_json: Detailed JSON with timestamps and word-level info

Text-to-Speech Optimization

Voice Selection:
- alloy/nova: General purpose
- echo/onyx: News and broadcasting
- fable/shimmer: Story narration
Speed Adjustment:
- Normal speed: 1.0
- Fast broadcast: 1.2 - 1.5
- Slow teaching: 0.75 - 0.9
Text Optimization:
- Max text length ≤4096 characters per request
- Use punctuation to control pauses and intonation
- Convert numbers and symbols to words
Cost Control:
- Use tts-1 for standard scenarios
- Use tts-1-hd for high-quality needs
- Choose appropriate model based on requirements

Error Handling

from openai import OpenAI
import time

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.yelinai.com/v1"
)

def transcribe_with_retry(audio_file_path, max_retries=3):
    """Audio transcription with retry mechanism"""
    for attempt in range(max_retries):
        try:
            with open(audio_file_path, "rb") as audio_file:
                transcript = client.audio.transcriptions.create(
                    model="gpt-4o-transcribe",
                    file=audio_file
                )
            return transcript.text
        except Exception as e:
            print(f"Attempt {attempt + 1}/{max_retries} failed: {e}")
            if attempt < max_retries - 1:
                time.sleep(2 ** attempt)  # Exponential backoff
            else:
                raise
    return None

📊 Performance Comparison

Speech-to-Text Models

Model	Accuracy	Speed	Languages	Billing	Price
gpt-4o-transcribe	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	50+	Token	$$
gpt-4o-mini-transcribe	⭐⭐⭐⭐	⭐⭐⭐⭐⭐	50+	Token	$
whisper-1	⭐⭐⭐⭐	⭐⭐⭐	50+	Duration	$

Text-to-Speech Models

Model	Quality	Speed	Naturalness	Price
tts-1	⭐⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	$
tts-1-hd	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐⭐⭐	$$

🚨 Important Notes

Privacy Protection: Don’t upload audio files with sensitive information
Compliance: Follow relevant laws and regulations, avoid illegal uses
Copyright Notice: Generated speech content should be marked as AI-generated
File Limits: Max audio file 25 MB, max text 4096 characters
Usage Restrictions: Do not use for impersonation or misinformation

Chat Completions API - Learn more about the Chat API
Pricing Information - View pricing details

💡 Tip: Start with gpt-4o-mini-transcribe or tts-1 for testing, then upgrade to premium models for production deployment.

Getting Started

Core API

Text APIs

Video Generation APIs

Image Generation APIs

AI Understanding

Audio Transcription & Speech Synthesis API | LaoZhang API

Overview

🌟 Key Features

📋 Supported Audio Models

Speech-to-Text (Transcription)

Text-to-Speech (TTS)

Available Voice Options

🎙️ Speech-to-Text

1. Basic Example - cURL

2. Python Example - Using OpenAI SDK

3. Specify Language and Response Format

4. Using Whisper Model (Duration-based Billing)

Supported Audio Formats

🗣️ Text-to-Speech

1. Basic Example - cURL

2. Python Example - Generate Audio File

3. Using HD Model

4. Adjust Speech Speed

5. Real-time Streaming Output

🎯 Common Use Cases

1. Meeting Transcription

2. Video Subtitle Generation

3. Multi-language Content Broadcasting

4. Audiobook Creation

💡 Best Practices

Speech-to-Text Optimization

Text-to-Speech Optimization

Error Handling

📊 Performance Comparison

Speech-to-Text Models

Text-to-Speech Models

🚨 Important Notes

Getting Started

Core API

Text APIs

Video Generation APIs

Image Generation APIs

AI Understanding

​ Overview

​ 🌟 Key Features

​ 📋 Supported Audio Models

​ Speech-to-Text (Transcription)

​ Text-to-Speech (TTS)

​ Available Voice Options

​ 🎙️ Speech-to-Text

​ 1. Basic Example - cURL

​ 2. Python Example - Using OpenAI SDK

​ 3. Specify Language and Response Format

​ 4. Using Whisper Model (Duration-based Billing)

​ Supported Audio Formats

​ 🗣️ Text-to-Speech

​ 1. Basic Example - cURL

​ 2. Python Example - Generate Audio File

​ 3. Using HD Model

​ 4. Adjust Speech Speed

​ 5. Real-time Streaming Output

​ 🎯 Common Use Cases

​ 1. Meeting Transcription

​ 2. Video Subtitle Generation

​ 3. Multi-language Content Broadcasting

​ 4. Audiobook Creation

​ 💡 Best Practices

​ Speech-to-Text Optimization

​ Text-to-Speech Optimization

​ Error Handling

​ 📊 Performance Comparison

​ Speech-to-Text Models

​ Text-to-Speech Models

​ 🚨 Important Notes

​ 🔗 Related Resources

Overview

🌟 Key Features

📋 Supported Audio Models

Speech-to-Text (Transcription)

Text-to-Speech (TTS)

Available Voice Options

🎙️ Speech-to-Text

1. Basic Example - cURL

2. Python Example - Using OpenAI SDK

3. Specify Language and Response Format

4. Using Whisper Model (Duration-based Billing)

Supported Audio Formats

🗣️ Text-to-Speech

1. Basic Example - cURL

2. Python Example - Generate Audio File

3. Using HD Model

4. Adjust Speech Speed

5. Real-time Streaming Output

🎯 Common Use Cases

1. Meeting Transcription

2. Video Subtitle Generation

3. Multi-language Content Broadcasting

4. Audiobook Creation

💡 Best Practices

Speech-to-Text Optimization

Text-to-Speech Optimization

Error Handling

📊 Performance Comparison

Speech-to-Text Models

Text-to-Speech Models

🚨 Important Notes

🔗 Related Resources