aidataservices.inAI data collection · India

Conversational speech · Accent Adaptation

Conversational Speech Data for Accent Adaptation

Natural two-party and multi-party conversation recorded with separate channels per speaker, covering the overlaps, interruptions and turn-taking that scripted data never produces. Applied to accent adaptation, the specification is driven by one thing: per-accent wer spread.

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Two speakers recording natural conversational speech data — Conversational Speech Data for Accent Adaptation
Service
Conversational speech
Use case
Accent Adaptation
Primary metric
Per-accent WER spread
01

Required data profile

  • Accent-band balanced speech with substrate-language tags
  • Matched content across bands for controlled comparison
Conversational speech — Accent Adaptation · written into the SOW before recordingChannelsOne channel per speaker, time-alignedDuration15-60 minutes per conversationTopicsScenario cards, free topics, or your domain scriptsOverlapPreserved and tagged, never edited outMetadataRelationship between speakers, familiarity, topic, settingYour values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
ChannelsOne channel per speaker, time-aligned
Duration15-60 minutes per conversation
TopicsScenario cards, free topics, or your domain scripts
OverlapPreserved and tagged, never edited out
MetadataRelationship between speakers, familiarity, topic, setting
Audio waveforms being prepared as ASR training data — supporting conversational speech data for accent adaptation
Audio waveforms being prepared as ASR training data
03

Process

  • Scenario design so conversations stay on-domain without becoming scripted
  • Speaker pairing by familiarity level as specified
  • Multi-channel recording with per-speaker isolation
  • Diarisation-ready packaging
  • Verbatim transcription with speaker turns and overlap tags
04

Metrics this feeds

  • Per-accent WER spread
  • Regression on the original accent set
05

Failure modes to design out

  • Treating Indian English as one accent
  • No substrate tagging, so the model cannot be evaluated per band

Conversations are checked for naturalness, not just audio quality. Sessions that drift into reading are rejected.

06

Deliverables

  • Per-speaker channels plus mixed reference
  • Turn-level transcripts
  • Overlap and backchannel tags
  • Conversation metadata

Frequently asked

Is conversational speech the right service for accent adaptation?

It covers accent-band balanced speech with substrate-language tags. Most accent adaptation 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 conversational speech for accent adaptation

Send the metric you need to move.

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