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Conversational speech · ASR Model Training

Conversational Speech Data for ASR Model Training

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 asr model training, the specification is driven by one thing: word error rate overall and per dialect.

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Audio waveforms being prepared as ASR training data — Conversational Speech Data for ASR Model Training
Service
Conversational speech
Use case
ASR Model Training
Primary metric
Word error rate overall and per dialect
01

Required data profile

  • Hundreds to thousands of hours of verbatim-transcribed speech
  • Wide speaker diversity: age, gender, region, education, recording condition
  • Speaker-disjoint train/dev/test splits
Conversational speech — ASR Model Training · 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
Annotators writing prompts and responses for LLM training data — supporting conversational speech data for asr model training
Annotators writing prompts and responses for LLM 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

  • Word error rate overall and per dialect
  • Entity error rate on names and numbers
  • Code-switch token accuracy
05

Failure modes to design out

  • Read-speech-only corpora that do not transfer to spontaneous audio
  • Speaker leakage across splits inflating reported accuracy
  • Normalised-only transcripts with the raw text discarded

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 asr model training?

It covers hundreds to thousands of hours of verbatim-transcribed speech. Most asr model training 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 asr model training

Send the metric you need to move.

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