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it will help you to send voice messages to your AI Assistant and also can make it talk

Text-to-Speech and Speech-to-Text using ElevenLabs AI. Use when the user wants to convert text to speech, transcribe voice messages, or work with voice in multiple languages. Supports high-quality AI voices and accurate transcription.

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name: elevenlabs-speech description: Text-to-Speech and Speech-to-Text using ElevenLabs AI. Use when the user wants to convert text to speech, transcribe voice messages, or work with voice in multiple languages. Supports high-quality AI voices and accurate transcription.

ElevenLabs Speech

Complete voice solution — both TTS and STT using one API:

  • TTS: Text-to-Speech (high-quality voices)
  • STT: Speech-to-Text via Scribe (accurate transcription)

Quick Start

Environment Setup

Set your API key:

export ELEVENLABS_API_KEY="sk_..."

Or create .env file in workspace root.

Text-to-Speech (TTS)

Convert text to natural-sounding speech:

python scripts/elevenlabs_speech.py tts -t "Hello world" -o greeting.mp3

With custom voice:

python scripts/elevenlabs_speech.py tts -t "Hello" -v "voice_id_here" -o output.mp3

List Available Voices

python scripts/elevenlabs_speech.py voices

Using in Code

from scripts.elevenlabs_speech import ElevenLabsClient
 
client = ElevenLabsClient(api_key="sk_...")
 
# Basic TTS
result = client.text_to_speech(
    text="Hello from zerox",
    output_path="greeting.mp3"
)
 
# With custom settings
result = client.text_to_speech(
    text="Your text here",
    voice_id="21m00Tcm4TlvDq8ikWAM",  # Rachel
    stability=0.5,
    similarity_boost=0.75,
    output_path="output.mp3"
)
 
# Get available voices
voices = client.get_voices()
for voice in voices['voices']:
    print(f"{voice['name']}: {voice['voice_id']}")
Voice ID Name Description
21m00Tcm4TlvDq8ikWAM Rachel Natural, versatile (default)
AZnzlk1XvdvUeBnXmlld Domi Strong, energetic
EXAVITQu4vr4xnSDxMaL Bella Soft, soothing
ErXwobaYiN019PkySvjV Antoni Well-rounded
MF3mGyEYCl7XYWbV9V6O Elli Warm, friendly
TxGEqnHWrfWFTfGW9XjX Josh Deep, calm
VR6AewLTigWG4xSOukaG Arnold Authoritative

Voice Settings

  • stability (0-1): Lower = more emotional, Higher = more stable
  • similarity_boost (0-1): Higher = closer to original voice

Default: stability=0.5, similarity_boost=0.75

Models

  • eleven_turbo_v2_5 - Fast, high quality (default)
  • eleven_multilingual_v2 - Best for non-English
  • eleven_monolingual_v1 - English only

Integration with Telegram

When user sends text and wants voice reply:

# Generate speech
result = client.text_to_speech(text=user_text, output_path="reply.mp3")
 
# Send via Telegram message tool with media path
message(action="send", media="path/to/reply.mp3", as_voice=True)

Pricing

Check https://elevenlabs.io/pricing for current rates. Free tier available!

Speech-to-Text (STT) with ElevenLabs Scribe

Transcribe voice messages using ElevenLabs Scribe:

Transcribe Audio

python scripts/elevenlabs_scribe.py voice_message.ogg

With specific language:

python scripts/elevenlabs_scribe.py voice_message.ogg --language ara

With speaker diarization (multiple speakers):

python scripts/elevenlabs_scribe.py voice_message.ogg --speakers 2

Using in Code

from scripts.elevenlabs_scribe import ElevenLabsScribe
 
client = ElevenLabsScribe(api_key="sk-...")
 
# Basic transcription
result = client.transcribe("voice_message.ogg")
print(result['text'])
 
# With language hint (improves accuracy)
result = client.transcribe("voice_message.ogg", language_code="ara")
 
# With speaker detection
result = client.transcribe("voice_message.ogg", num_speakers=2)

Supported Formats

  • mp3, mp4, mpeg, mpga, m4a, wav, webm
  • Max file size: 100 MB
  • Works great with Telegram voice messages (.ogg)

Language Support

Scribe supports 99 languages including:

  • Arabic (ara)
  • English (eng)
  • Spanish (spa)
  • French (fra)
  • And many more...

Without language hint, it auto-detects.

Complete Workflow Example

User sends voice message → You reply with voice:

from scripts.elevenlabs_scribe import ElevenLabsScribe
from scripts.elevenlabs_speech import ElevenLabsClient
 
# 1. Transcribe user's voice message
stt = ElevenLabsScribe()
transcription = stt.transcribe("user_voice.ogg")
user_text = transcription['text']
 
# 2. Process/understand the text
# ... your logic here ...
 
# 3. Generate response text
response_text = "Your response here"
 
# 4. Convert to speech
tts = ElevenLabsClient()
tts.text_to_speech(response_text, output_path="reply.mp3")
 
# 5. Send voice reply
message(action="send", media="reply.mp3", as_voice=True)

Pricing

Check https://elevenlabs.io/pricing for current rates:

TTS (Text-to-Speech):

  • Free tier: 10,000 characters/month
  • Paid plans available

STT (Speech-to-Text) - Scribe:

  • Free tier available
  • Check website for current pricing