ASR datasets · Code-Switching ASR
ASR Training Data for Code-Switching ASR
Transcribed speech corpora built to train and evaluate automatic speech recognition, with verbatim transcription, timestamps and per-token language tagging where code-mixing occurs. Applied to code-switching asr, the specification is driven by one thing: switch-point accuracy.
- Service
- ASR datasets
- Use case
- Code-Switching ASR
- Primary metric
- Switch-point accuracy
Required data profile
- Genuinely code-mixed spontaneous speech
- Per-token language ID labels
- A fixed rule for script of English tokens
Technical specification
| Parameter | Standard |
|---|---|
| Audio | 16 kHz or 48 kHz PCM WAV |
| Transcription | Verbatim, including disfluencies, false starts and fillers |
| Timestamps | Utterance level by default; word level on request |
| Tagging | Noise, overlap, unintelligible, foreign-language and code-switch tags |
| Normalisation | Raw and normalised text columns delivered separately |
| Split | Train/dev/test splits with no speaker leakage across splits |
Process
- Style guide authored per language, covering numerals, loanwords, script and disfluency rules
- Transcriber calibration round with inter-annotator agreement measurement
- First-pass transcription
- Second-pass native review
- Automated consistency checks against the style guide
- Split generation with speaker-disjoint partitions
Metrics this feeds
- Switch-point accuracy
- Mixed-utterance WER
- Language ID token accuracy
Failure modes to design out
- Concatenating monolingual data and calling it code-mixed
- Leaving script conventions to individual annotators
Agreement is measured, not assumed. We report word-level agreement on a held-out sample so you can judge label quality before training on it.
Deliverables
- Audio plus aligned transcripts (JSON/TSV, or your schema)
- Style guide as delivered documentation
- Inter-annotator agreement report
- Speaker-disjoint train/dev/test splits
Frequently asked
Is asr datasets the right service for code-switching asr?
It covers genuinely code-mixed spontaneous speech. Most code-switching asr programmes combine it with at least one other service; we will say so in the scope rather than selling one line item.
What languages are available?
All 14 languages in the network plus Indian English accent bands.
How is the evaluation set handled?
Collected first, from speakers disjoint from the training cohort, so improvement is measurable.
Scope asr datasets for code-switching asr
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