How is Command Data Structured for Use in Speech Recognition Models?

Command data for speech recognition models is typically structured with the following elements:

1. Audio Files: Recordings of spoken commands in formats like WAV or MP3, including diverse accents and environments.

2. Transcriptions: Text representations of the spoken commands, standardized for consistency.

3. Metadata: Information about the speaker (age, gender, accent) and recording conditions (background noise, distance from the microphone).

4. Labels: Categorization of commands (e.g., control, navigation) and inclusion of both valid and similar-sounding phrases.

5. Data Splits: Division into training, validation, and test sets to evaluate model performance.

6. File Naming Conventions: Consistent naming for easy matching of audio files and transcriptions.

7. Usage Context: Additional context about command usage may be included to improve understanding.

This structured approach helps in effectively training speech recognition models for accurate command processing.