ASR datasets · ਪੰਜਾਬੀ
Punjabi ASR Training Data
Transcribed speech corpora built to train and evaluate automatic speech recognition, with verbatim transcription, timestamps and per-token language tagging where code-mixing occurs. This page covers how that works specifically for Punjabi, where punjabi is tonal: high, low and level tones distinguish words, and tone is not marked in gurmukhi orthography.
- Language
- Punjabi (pa-IN)
- Dialects covered
- 5
- Typical programme
- 100-500 hours
- Cities
- Amritsar, Ludhiana, Jalandhar
What changes when the language is Punjabi
The service specification stays constant across languages; the linguistics do not. For Punjabi, three things drive the design of a asr datasets programme.
- Punjabi is tonal: high, low and level tones distinguish words, and tone is not marked in Gurmukhi orthography
- Dialect spread: Majhi (standard), Malwai, Doabi, Puadhi
- Punjabi speech mixes Hindi and English freely, with strong diaspora influence in urban registers.
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 |
Punjabi cohort design
Cover all three historic regions (Majha, Malwa, Doaba); tone realisation differs measurably between them.
| Dimension | Typical split | Why it matters for Punjabi |
|---|---|---|
| Gender | 50 / 50 | Pitch range differences change acoustic model behaviour; unbalanced cohorts bias recognition |
| Age | 18-25: 30%, 26-40: 40%, 41-60: 30% | Older speakers retain conservative Punjabi forms that younger urban speakers have lost |
| Region | Punjab / Haryana / Delhi and others | Dialect spread across 5 recognised varieties |
| Education | Mixed, including below-graduate | Prompt-reading fluency correlates with education and skews prosody |
| Condition | Studio / quiet room / field | Match the noise profile of your deployment |
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
Punjabi-specific quality rules
- Tone is unrepresented in text, so pronunciation lexicons must be built from audio, not from spelling
- Shahmukhi vs Gurmukhi script decisions must be fixed per project
- Adhak (gemination) applied inconsistently
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
Worked example
A representative Punjabi asr datasets engagement: 100 hours from 300 speakers, 50/50 gender, ages 18-45, spread across Amritsar, Ludhiana, Jalandhar, recorded to the specification above and delivered in WAV with a per-utterance manifest.
Timeline: Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
Where this data is missing today
Tonal variation is essentially unmodelled in public Punjabi data, and Malwai/Doabi rural speech is scarce.
Frequently asked
How much does Punjabi asr datasets cost?
Priced per delivered hour or unit against a written spec. The cost drivers for Punjabi are dialect spread, demographic narrowness and recording condition, in that order.
Which Punjabi dialects are included?
By default Majhi (standard), Malwai, Doabi, Puadhi and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.
Can you deliver Punjabi data in our format?
Yes. Audio plus aligned transcripts (JSON/TSV, or your schema) is the default, but naming, schema and directory structure follow your pipeline.
How long does a Punjabi programme take?
Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
Request a Punjabi asr datasets quote
Hours, speakers, dialects, deadline. Send what you have.