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Audio Analysis

Transcribe audio and analyze sentiment from spoken content.

Usage

async with Sentimatrix() as sm:
    result = await sm.analyze_audio("customer_call.wav")

    print(f"Transcription: {result.transcription}")
    print(f"Sentiment: {result.sentiment.label}")
    print(f"Emotions: {result.emotions.top_k(3)}")

Supported Formats

  • WAV
  • MP3
  • FLAC
  • OGG
  • M4A

Transcription Engines

Engine Speed Quality Provider
whisper-base Fast Good Local
whisper-medium Medium Better Local
whisper-large-v3 Slow Best Local
groq-whisper Fast Excellent Groq API

Configuration

from sentimatrix.config import SentimatrixConfig, LLMConfig

config = SentimatrixConfig(
    llm=LLMConfig(provider="groq")  # For Groq Whisper
)

async with Sentimatrix(config) as sm:
    result = await sm.analyze_audio(
        "call.wav",
        engine="groq-whisper"
    )

Use Cases

  • Call center analysis
  • Voice feedback processing
  • Podcast sentiment
  • Meeting summaries