ASR datasets · മലയാളം
Malayalam 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 Malayalam, where one of the most consonant-dense indian languages; long geminates and clusters raise word error rates sharply.
- Language
- Malayalam (ml-IN)
- Dialects covered
- 5
- Typical programme
- 100-500 hours
- Cities
- Kochi, Thiruvananthapuram, Kozhikode
What changes when the language is Malayalam
The service specification stays constant across languages; the linguistics do not. For Malayalam, three things drive the design of a asr datasets programme.
- One of the most consonant-dense Indian languages; long geminates and clusters raise word error rates sharply
- Dialect spread: Thiruvananthapuram, Kochi (central), Malabar / Kozhikode, Thrissur
- Manglish is standard in urban and professional speech, with heavy English noun and verb insertion.
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 |
Malayalam cohort design
Budget higher transcription effort per audio hour for Malayalam than for Hindi; speech rate and morphology make it slower to annotate.
| Dimension | Typical split | Why it matters for Malayalam |
|---|---|---|
| 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 Malayalam forms that younger urban speakers have lost |
| Region | Kerala / Lakshadweep / Puducherry (Mahe) 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
Malayalam-specific quality rules
- Old vs new script (chillu characters, Unicode normalisation) mixed within a dataset
- Fast speech leads to dropped-word transcription errors without a second-pass QA
- Dialect vocabulary from Malabar standardised away
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 Malayalam asr datasets engagement: 100 hours from 300 speakers, 50/50 gender, ages 18-45, spread across Kochi, Thiruvananthapuram, Kozhikode, 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
Central Kerala news-reading dominates public data. Malabar and southern varieties, and fast conversational speech generally, are missing.
Frequently asked
How much does Malayalam asr datasets cost?
Priced per delivered hour or unit against a written spec. The cost drivers for Malayalam are dialect spread, demographic narrowness and recording condition, in that order.
Which Malayalam dialects are included?
By default Thiruvananthapuram, Kochi (central), Malabar / Kozhikode, Thrissur and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.
Can you deliver Malayalam 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 Malayalam programme take?
Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.
Request a Malayalam asr datasets quote
Hours, speakers, dialects, deadline. Send what you have.