---

name: data-audio-pipelines description: "Guides SpeechBrain audio I/O, DynamicItemDataset and DataPipeline construction, encoders/tokenizers, feature extraction, augmentation, beamforming, and preprocessing troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

SpeechBrain data and audio pipelines

Use this sub-skill when the task involves audio loading/saving, dataset manifests, dynamic item pipelines, encoders/tokenizers, preprocessing, augmentation, feature extraction, beamforming, or vocal features.

Route map

Task	Read/run
Audio load/save/info, shape debugging, SoundFile backend behavior.	references/audio-and-features.md; run scripts/audio_io_roundtrip.py.
Build DynamicItemDataset, DataPipeline, takes, provides, output keys, or data manifests.	references/data-pipelines.md; run scripts/dynamic_pipeline_smoke.py.
Train/use SentencePiece or categorical/text/CTC encoders.	references/data-pipelines.md.
Use STFT, filterbanks, MFCCs, normalization, streaming features, or tensor shape conventions.	references/audio-and-features.md.
Use AddNoise, AddReverb, SpeedPerturb, DropFreq, DropChunk, clipping, beamforming, or vocal feature extraction.	references/augmentation-and-preprocessing.md.
Diagnose audio/data/preprocessing failures.	references/troubleshooting.md.

Key conventions

• Audio I/O is through speechbrain.dataio.audio_io and uses SoundFile.
• audio_io.load returns (tensor, sample_rate) and can use channels_first / always_2d to control shape.
• SpeechBrain model tensors generally use batch first and time second: (batch, time) or (batch, time, channels).
• DynamicItemDataset plus DataPipeline lets recipes compute derived fields lazily from static manifest keys.
• Dynamic item functions declare dependencies with @takes(...) and outputs with @provides(...).
• Output keys control which dynamic items are executed; omitted outputs may prevent a dynamic item from running at all.

Safe smoke checks

python scripts/audio_io_roundtrip.py --json
python scripts/dynamic_pipeline_smoke.py --json

Both scripts use synthetic data only and do not require a SpeechBrain source checkout, dataset, network, or GPU.