aidataservices.inAI data collection · India

ASR datasets · বাংলা

Bengali 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 Bengali, where inherent vowel is realised as /ɔ/ or /o/, which breaks g2p rules copied from devanagari-based systems.

Request a dataset quoteReply within one working day
Audio waveforms being prepared as ASR training data — Bengali ASR Training Data
Language
Bengali (bn-IN)
Dialects covered
5
Typical programme
500-2,000 hours
Cities
Kolkata, Siliguri, Durgapur
01

What changes when the language is Bengali

The service specification stays constant across languages; the linguistics do not. For Bengali, three things drive the design of a asr datasets programme.

  • Inherent vowel is realised as /ɔ/ or /o/, which breaks G2P rules copied from Devanagari-based systems
  • Dialect spread: Kolkata standard (Rarhi), Sylheti-influenced, Rangpuri / North Bengal, Medinipuri
  • Kolkata professional speech mixes English heavily; rural West Bengal much less. A single 'Bengali' dataset without register tags conflates two very different acoustic and lexical distributions.
ASR datasets — Bengali · written into the SOW before recordingAudio16 kHz or 48 kHz PCM WAVTranscriptionVerbatim, including disfluencies, false starts and fillersTimestampsUtterance level by default; word level on requestTaggingNoise, overlap, unintelligible, foreign-language and code-s…NormalisationRaw and normalised text columns delivered separatelyYour values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
Audio16 kHz or 48 kHz PCM WAV
TranscriptionVerbatim, including disfluencies, false starts and fillers
TimestampsUtterance level by default; word level on request
TaggingNoise, overlap, unintelligible, foreign-language and code-switch tags
NormalisationRaw and normalised text columns delivered separately
SplitTrain/dev/test splits with no speaker leakage across splits
Speaker recording scripted prompts for a speech data collection project — supporting bengali asr training data
Speaker recording scripted prompts for a speech data collection project
03

Bengali cohort design

Tag every speaker as Indian Bengali and record district of origin; mixing in Bangladeshi speech without tags is a common and costly dataset defect.

DimensionTypical splitWhy it matters for Bengali
Gender50 / 50Pitch range differences change acoustic model behaviour; unbalanced cohorts bias recognition
Age18-25: 30%, 26-40: 40%, 41-60: 30%Older speakers retain conservative Bengali forms that younger urban speakers have lost
RegionWest Bengal / Tripura / Assam (Barak Valley) and othersDialect spread across 5 recognised varieties
EducationMixed, including below-graduatePrompt-reading fluency correlates with education and skews prosody
ConditionStudio / quiet room / fieldMatch the noise profile of your deployment
04

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
05

Bengali-specific quality rules

  • Three sibilant characters chosen inconsistently for the same sound
  • Bangladeshi vs Indian Bengali orthographic conventions mixed within one dataset
  • Verb conjugation register (cholit vs sadhu) normalised by transcribers

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.

06

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
07

Worked example

A representative Bengali asr datasets engagement: 500 hours from 1,000 speakers, 50/50 gender, ages 18-45, spread across Kolkata, Siliguri, Durgapur, 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.

08

Where this data is missing today

Indian Bengali is under-collected relative to Bangladeshi Bengali, and North Bengal and Tripura varieties are almost entirely missing.

Frequently asked

How much does Bengali asr datasets cost?

Priced per delivered hour or unit against a written spec. The cost drivers for Bengali are dialect spread, demographic narrowness and recording condition, in that order.

Which Bengali dialects are included?

By default Kolkata standard (Rarhi), Sylheti-influenced, Rangpuri / North Bengal, Medinipuri and others, tagged per speaker. You can also commission a single-dialect corpus if you are targeting one region.

Can you deliver Bengali 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 Bengali programme take?

Transcription adds roughly 1-2 weeks per 100 hours after recording, per language.

Request a Bengali asr datasets quote

Hours, speakers, dialects, deadline. Send what you have.

Request a dataset quote