Amey-Thakur Audio processing
Recorded audio arrives at wildly different levels, sample rates, and quality. Without normalisation the listener adjusts volume between clips, and downstream processing such as transcription degrades on the quiet ones.
Method
- Normalise loudness to a standard. Perceptual loudness normalisation rather than peak, since peak-normalised audio still varies in perceived volume between recordings.
- Resample to one rate and channel layout. A consistent internal format simplifies every later stage, and speech rarely benefits from high rates or stereo.
- Choose bitrate by content. Speech is intelligible at rates far below music, and using a music bitrate for spoken content wastes most of the bytes.
- Trim silence at the edges, carefully. Leading and trailing silence wastes time and storage, while aggressive trimming clips the first word.
- Preserve the original for reprocessing. Transcription models and codecs improve, and reprocessing from a compressed derivative compounds loss.
- Extract duration and waveform data at ingest. Both are needed by the interface immediately and are cheap during a pass you are already making.
- Prepare deliberately for transcription. Mono, a suitable sample rate, and normalised levels materially improve accuracy (see document-parsing for the analogous extraction concern).
Boundaries
Processing improves consistency; it cannot recover information a poor recording never captured. Aggressive noise reduction introduces artefacts that harm both listening and transcription. Voice recordings are personal data and often biometric, with heightened obligations (see data-classification).