Speech/tools/speech_data_explorer at main · NVIDIA-NeMo/Speech
Speech Data Explorer
-based tool for interactive exploration of ASR/TTS datasets.
Features:
dataset's statistics (alphabet, vocabulary, duration-based histograms)
navigation across dataset (sorting, filtering)
inspection of individual utterances (waveform, spectrogram, audio player)
errors' analysis (Word Error Rate, Character Error Rate, Word Match Rate, Mean Word Accuracy, diff)
comparison of two ASR models using interactive word-level accuracy plot
read manifests and audio directly from S3-compatible storage (including AIStore)
support for tarred audio datasets with efficient byte-range reads via DALI index files
Quick Start
Install the requirements:
pip install -r requirements.txt Run with a local manifest:
python data_explorer.py path_to_manifest.json S3 / AIStore Support
Speech Data Explorer can read manifests and audio files directly from S3-compatible object storage, including NVIDIA AIStore (AIS).
Using an S3 config file
python data_explorer.py s3://bucket/manifest.json --s3cfg ~/.s3cfg[default] Using AIStore with environment variables
export AIS_ENDPOINT=http://ais-gateway:8080 export AIS_AUTHN_TOKEN=your_token python data_explorer.py s3://bucket/manifest.json --s3cfg AIS Sharded paths (_OP_/_CL_ syntax)
Manifests and tar files are often split into numbered shards. Instead of listing every shard explicitly, use the _OP_start..end_CL_ range pattern. The tool expands it into individual paths automatically:
s3://bucket/manifest__OP_0..255_CL_.json → s3://bucket/manifest_0.json s3://bucket/manifest_1.json ... s3://bucket/manifest_255.json Multiple ranges in a single path produce a cartesian product — useful when shards are spread across several buckets or directories:
s3://store_OP_1..2_CL_/audio__OP_0..1_CL_.tar → s3://store1/audio_0.tar s3://store1/audio_1.tar s3://store2/audio_0.tar s3://store2/audio_1.tar Tarred audio
When audio is stored in tar archives locally or on S3, use --tar-base-path to point to the tar files. DALI index files are used automatically (if available at <tar_dir>/dali_index/) for fast byte-range lookups:
python data_explorer.py /data/manifests/manifest.json \ --tar-base-path /data/tarred/audio.tar python data_explorer.py s3://bucket/manifests/manifest__OP_0..255_CL_.json \ --tar-base-path s3://bucket/tarred/audio__OP_0..255_CL_.tar \ --s3cfg ~/.s3cfg[default] You can also specify a custom DALI index location:
python data_explorer.py s3://bucket/manifest.json \ --tar-base-path s3://bucket/tarred/audio__OP_0..255_CL_.tar \ --dali-index-base s3://bucket/tarred/dali_index/ \ --s3cfg ~/.s3cfg[default] Comparing Two ASR Models
Single manifest with two prediction fields
If your manifest contains two pred_text_* fields (e.g. pred_text_contextnet and pred_text_conformer):
python data_explorer.py path_to_manifest.json \ -nc pred_text_contextnet pred_text_conformer Two separate manifests
You can also pass two separate manifests (order-invariant). Each manifest must contain a plain pred_text field, and -nc names the models:
python data_explorer.py manifest_model_A.json manifest_model_B.json \ -nc pred_text_model_A pred_text_model_B Manifest Format
JSON manifest file should contain the following fields:
audio_filepath — path to audio file (local path, or filename inside a tar archive when using --tar-base-path)
duration — duration of the audio file in seconds
text — reference transcript
Errors' analysis requires pred_text (ASR transcript) for all utterances.
Any additional field will be parsed and displayed in the Samples tab.
Additional Options
FlagDescription--vocabVocabulary file to highlight OOV words--portServing port (default: 8050)--estimate-audio-metrics / -aEstimate audio metrics--base-pathBase path for relative audio paths in the manifest--tar-base-pathLocal or S3 path to tarred audio files (supports sharded _OP_..._CL_ patterns)--dali-index-baseLocal or S3 path to DALI index directory for fast tar lookups--s3cfg / -s3cS3 config file and section, or AIS for AIStore env vars--force / -fTolerate manifest entries with missing required fields-nc / --names_comparedTwo field names for model comparison--show_statistics / -shstField name to show statistics for--debug / -dEnable debug mode
