Speaker Intelligence
Sentiment Analysis
Analyses the sentiment of the full transcript using Gemini. Returns label, numeric score (-1 to 1), and explanation.
Python SDK
python
config = TranscriptionConfig(
model="zero-indic",
enable_sentiment_analysis=True,
)
result = await client.asr.transcribe("feedback.wav", config=config)
s = result.nlp_analysis.sentiment
print(f"{s.label} | score: {s.score}")
# negative | score: -0.72
print(s.explanation)
# Customer expresses frustration about the vehicle being stranded.REST API
terminal
curl -X POST https://asr.shunyalabs.ai/v1/audio/transcriptions \
-H "Authorization: Bearer <API_KEY>" \
-F "[email protected]" \
-F "model=zero-indic" \
-F "enable_sentiment_analysis=true"Output
json
{
"nlp_analysis": {
"sentiment": {
"label": "negative",
"score": -0.72,
"explanation": "Customer expresses frustration about the vehicle being stranded."
}
}
}