SPeech & Audio

Acoustic Scene and Emotion Detection Data

Labeled audio datasets for acoustic scene classification, emotion detection, and sound event recognition , enabling more context-aware and emotionally intelligent AI.

Understanding a spoken utterance means understanding its context. Where was it recorded? What is the speaker feeling? What background events are occurring? Appen's acoustic scene and emotion detection data service provides the labelled audio that teaches models to answer these questions, delivering the environmental and emotional awareness that smart speaker systems, call analytics platforms, and ambient intelligence devices require.

What Appen Delivers

Acoustic Scene Classification

Labeling of background acoustic environments including indoor spaces, outdoor settings, transportation, crowds, and industrial environments. Acoustic scene labels enable models to adapt their processing to context, improving noise suppression, speech enhancement, and situational awareness in unpredictable real-world conditions.

Speaker Emotion and Sentiment Labeling

Utterance-level and segment-level annotation of emotional state across categories including happiness, frustration, sadness, surprise, and neutral. Annotators are trained using sociophonetics frameworks that distinguish genuine emotional expression from performed affect, improving the ecological validity of emotion detection models.

Arousal and Valence Scoring

Dimensional emotion annotation using arousal-valence models, providing continuous rather than categorical emotional labels for applications requiring nuanced sentiment gradation. Dimensional annotation enables more precise emotion detection than discrete category labeling alone.

Multi-Channel Audio Annotation

Annotation of recordings from microphone arrays, binaural systems, and multi-speaker environments, supporting models that must locate, separate, and understand multiple concurrent audio sources.

Applications

Acoustic scene and emotion detection data supports call centre analytics platforms detecting customer frustration, in-cabin monitoring systems assessing driver alertness, smart home devices adapting behaviour to household context, and health monitoring applications tracking vocal indicators of wellbeing.

Appen has delivered acoustic annotation programmes for CallMiner's large-scale annotation and similar enterprise speech intelligence platforms. Our paralinguistic event labeling service extends acoustic annotation to include non-verbal events including laughter, sighs, and hesitations.

Related Resources

Blog

What Is Sociophonetics and Why It Matters for AI

Sociophonetics explains how accent, rhythm, and pronunciation encode social meaning. Learn why this matters for ASR/TTS fairness - plus how Appen’s audio data expertise reduces accent bias and improve model accuracy.

Read article

Blog

An Introduction to Audio, Speech, and Language Processing

Applying Machine Learning to Everyday Scenarios. Human-machine-interaction is increasingly ubiquitous as technologies leveraging audio and language for artificial intelligence evolve.

Watch now

Case Study

CallMiner Delivers Fast and Accurate Customer Insights with Large-Scale Annotation Solution

The Appen Data Annotation Platform enables CallMiner to better serve its customers