speech to speech api with python library | ElevenLabs | Page 1

low crownBOT Nov 4, 2024, 8:47 AM

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AI-generated Answer for daezel

To use the Speech-to-Speech API with Python, you can follow the example below. This code demonstrates how to convert speech from one voice to another using the ElevenLabs API:

import requests
import json

# Define constants for the script
CHUNK_SIZE = 1024  # Size of chunks to read/write at a time
XI_API_KEY = "<xi-api-key>"  # Your API key for authentication
VOICE_ID = "<voice-id>"  # ID of the voice model to use
AUDIO_FILE_PATH = "<path>"  # Path to the input audio file
OUTPUT_PATH = "output.mp3"  # Path to save the output audio file

# Construct the URL for the Speech-to-Speech API request
sts_url = f"https://api.elevenlabs.io/v1/speech-to-speech/{VOICE_ID}/stream"

# Set up headers for the API request, including the API key for authentication
headers = {
    "Accept": "application/json",
    "xi-api-key": XI_API_KEY
}

# Set up the data payload for the API request, including model ID and voice settings
data = {
    "model_id": "eleven_english_sts_v2",
    "voice_settings": json.dumps({
        "stability": 0.5,
        "similarity_boost": 0.8,
        "style": 0.0,
        "use_speaker_boost": True
    })
}

# Set up the files to send with the request, including the input audio file
files = {
    "audio": open(AUDIO_FILE_PATH, "rb")
}

# Make the POST request to the STS API with headers, data, and files, enabling streaming response
response = requests.post(sts_url, headers=headers, data=data, files=files, stream=True)

# Check if the request was successful
if response.ok:
    # Open the output file in write-binary mode
    with open(OUTPUT_PATH, "wb") as f:
        # Read the response in chunks and write to the file
        for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
            f.write(chunk)
    # Inform the user of success
    print("Audio stream saved successfully.")
else:
    # Print the error message if the request was not successful
    print(response.text)

Make sure to replace placeholders like <xi-api-key>, <voice-id>, and <path> with your actual API key, voice ID, and the path to your input audio file, respectively. Adjust paths and settings as needed.

sinful path Nov 4, 2024, 8:49 AM

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this is just straight up python. what about using the library?

low crownBOT Nov 4, 2024, 8:49 AM

#

AI-generated Answer for daezel

To use the ElevenLabs Python library for speech-to-speech conversion, you can follow these steps:

Install the ElevenLabs SDK: First, ensure you have the ElevenLabs SDK installed. You can do this using pip:
```
pip install elevenlabs
```
Set Up Your Environment: Create a .env file in your project directory and add your API key:
```
ELEVENLABS_API_KEY=your_elevenlabs_api_key_here
```

Use the SDK for Speech-to-Speech: Here's a basic example of how you might set up a script to perform speech-to-speech conversion using the ElevenLabs SDK:

import os
from elevenlabs import ElevenLabs
from dotenv import load_dotenv

# Load the API key from the .env file
load_dotenv()
ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")

# Initialize the ElevenLabs client
client = ElevenLabs(api_key=ELEVENLABS_API_KEY)

# Define the voice ID and audio file path
voice_id = "<voice-id>"
audio_file_path = "<path-to-your-audio-file>"

# Perform the speech-to-speech conversion
with open(audio_file_path, "rb") as audio_file:
    response = client.speech_to_speech.convert(
        voice_id=voice_id,
        audio=audio_file,
        model_id="eleven_english_sts_v2",
        voice_settings={
            "stability": 0.5,
            "similarity_boost": 0.8,
            "style": 0.0,
            "use_speaker_boost": True
        }
    )

# Save the output audio
with open("output.mp3", "wb") as output_file:
    output_file.write(response.content)

print("Audio stream saved successfully.")

Make sure to replace placeholders like <voice-id> and <path-to-your-audio-file> with your actual voice ID and the path to your audio file. Adjust the settings as needed for your specific use case.

sinful path Nov 4, 2024, 9:17 AM

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looks like speech to speech api is returning generator object?

low crownBOT Nov 4, 2024, 9:17 AM

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AI-generated Answer for daezel

The Speech-to-Speech API in Python involves making HTTP requests directly, as shown in the example code. If you're using a library that returns a generator object, it might be handling the streaming response for you.

In the provided example, the response.iter_content(chunk_size=CHUNK_SIZE) is used to stream the audio data in chunks. This is typical when dealing with large data streams, allowing you to process the data incrementally rather than loading it all into memory at once.

If you're using a specific Python library that wraps around the API, it might abstract this process and return a generator object to iterate over the streamed data. You can handle it similarly by iterating over the generator to process or save the audio data. If you need more specific guidance, please provide details about the library you're using.

sinful path Nov 4, 2024, 9:22 AM

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def generate_tts_with_emotion(data):
text = data.get('text')
role_voice_id = data.get('role_voice_id')
emotion_voice_id = data.get('emotion_voice_id')
stability = data.get('stability')
similarity_boost = data.get('similarity_boost')
style = data.get('style')

if not all([text, role_voice_id, emotion_voice_id]):
    raise ValueError("Text, role_voice_id, and emotion_voice_id are required")


voice_settings = VoiceSettings(
    stability=stability,
    similarity_boost=similarity_boost,
    style=style,
    use_speaker_boost=True
)

initial_audio = client.text_to_speech.convert(
    voice_id=emotion_voice_id,
    optimize_streaming_latency="0",
    output_format="mp3_22050_32",
    text=text,
    voice_settings=voice_settings,
    model_id="eleven_multilingual_v2"
)


initial_audio_bytes = b''.join(initial_audio)


audio_file = BytesIO(initial_audio_bytes)


final_audio = client.speech_to_speech.convert(
    voice_id=role_voice_id,
    audio=audio_file,
    model_id="eleven_english_sts_v2",
    voice_settings={
        "stability": stability,
        "similarity_boost": similarity_boost,
        "style": style,
        "use_speaker_boost": True
    }
)


final_audio_bytes = b''.join(final_audio)

return final_audio_bytes, generate_unique_filename(text) + ".mp3"

2024-11-04 18:20:54 ERROR: Error generating TTS: Invalid type for value. Expected primitive type, got <class 'dict'>: {'stability': 0.5, 'similarity_boost': 0.5, 'style': 0.5, 'use_speaker_boost': True}

low crownBOT Nov 4, 2024, 9:22 AM

#

AI-generated Answer for daezel

The error you're encountering suggests that the voice_settings parameter in the speech_to_speech.convert method is expecting a different data type than what is being provided. It seems like the method is expecting a primitive type rather than a dictionary.

To resolve this, you should ensure that the voice_settings parameter is correctly formatted according to the API's requirements. If the API expects individual parameters rather than a dictionary, you might need to pass them separately. Here's a revised version of your function:

def generate_tts_with_emotion(data):
    text = data.get('text')
    role_voice_id = data.get('role_voice_id')
    emotion_voice_id = data.get('emotion_voice_id')
    stability = data.get('stability')
    similarity_boost = data.get('similarity_boost')
    style = data.get('style')

    if not all([text, role_voice_id, emotion_voice_id]):
        raise ValueError("Text, role_voice_id, and emotion_voice_id are required")

    voice_settings = VoiceSettings(
        stability=stability,
        similarity_boost=similarity_boost,
        style=style,
        use_speaker_boost=True
    )

    initial_audio = client.text_to_speech.convert(
        voice_id=emotion_voice_id,
        optimize_streaming_latency="0",
        output_format="mp3_22050_32",
        text=text,
        voice_settings=voice_settings,
        model_id="eleven_multilingual_v2"
    )

    initial_audio_bytes = b''.join(initial_audio)

    audio_file = BytesIO(initial_audio_bytes)

    final_audio = client.speech_to_speech.convert(
        voice_id=role_voice_id,
        audio=audio_file,
        model_id="eleven_english_sts_v2",
        stability=stability,
        similarity_boost=similarity_boost,
        style=style,
        use_speaker_boost=True
    )

    final_audio_bytes = b''.join(final_audio)
    
    return final_audio_bytes, generate_unique_filename(text) + ".mp3"

In this version, the stability, similarity_boost, style, and use_speaker_boost parameters are passed directly to the speech_to_speech.convert method instead of being wrapped in a dictionary. Adjust the parameters as needed based on the API documentation.

sinful path Nov 4, 2024, 9:23 AM

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2024-11-04 18:23:24 ERROR: Error generating TTS: SpeechToSpeechClient.convert() got an unexpected keyword argument 'stability'

low crownBOT Nov 4, 2024, 9:23 AM

#

AI-generated Answer for daezel

It seems like you're encountering an error due to incorrect usage of the SpeechToSpeechClient.convert() method. The error message indicates that the method does not accept a keyword argument named stability.

To resolve this, ensure that the voice_settings parameter is passed as a JSON-encoded string, as required by the API. Here's a revised version of your function:

from io import BytesIO
import json

def generate_tts_with_emotion(data):
    text = data.get('text')
    role_voice_id = data.get('role_voice_id')
    emotion_voice_id = data.get('emotion_voice_id')
    stability = data.get('stability')
    similarity_boost = data.get('similarity_boost')
    style = data.get('style')

    if not all([text, role_voice_id, emotion_voice_id]):
        raise ValueError("Text, role_voice_id, and emotion_voice_id are required")

    voice_settings = {
        "stability": stability,
        "similarity_boost": similarity_boost,
        "style": style,
        "use_speaker_boost": True
    }

    initial_audio = client.text_to_speech.convert(
        voice_id=emotion_voice_id,
        optimize_streaming_latency="0",
        output_format="mp3_22050_32",
        text=text,
        voice_settings=voice_settings,
        model_id="eleven_multilingual_v2"
    )

    initial_audio_bytes = b''.join(initial_audio)

    audio_file = BytesIO(initial_audio_bytes)

    final_audio = client.speech_to_speech.convert(
        voice_id=role_voice_id,
        audio=audio_file,
        model_id="eleven_english_sts_v2",
        voice_settings=json.dumps(voice_settings)  # Convert to JSON string
    )

    final_audio_bytes = b''.join(final_audio)
    
    return final_audio_bytes, generate_unique_filename(text) + ".mp3"

Make sure to convert the voice_settings dictionary to a JSON string using json.dumps() before passing it to the speech_to_speech.convert() method. This should resolve the error you're encountering.

sinful path Nov 4, 2024, 9:42 AM

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what are the options of model i can use for speech to speech

#speech to speech api with python library