aidataservices.inAI data collection · India

TTS datasets · Speaker Diarisation

TTS Training Data for Speaker Diarisation

Single-speaker and multi-speaker text-to-speech corpora with phonetically balanced scripts, consistent prosody, and studio-grade capture suitable for neural TTS. Applied to speaker diarisation, the specification is driven by one thing: diarisation error rate.

Request a dataset quoteReply within one working day
Annotator labelling audio segments and speaker turns — TTS Training Data for Speaker Diarisation
Service
TTS datasets
Use case
Speaker Diarisation
Primary metric
Diarisation error rate
01

Required data profile

  • Per-speaker isolated channels with a mixed reference
  • Genuine overlap preserved
  • Turn-level ground truth
TTS datasets — Speaker Diarisation · written into the SOW before recordingSample rate48 kHz, 24-bitSpeaker consistencySame booth, mic, distance and time-of-day banding across se…ScriptPhonetically balanced, diphone-covering, domain-extendedProsodyNeutral base set plus optional expressive stylesAlignmentText-audio alignment verified per utteranceYour values replace ours rather than being converted after delivery.
02

Technical specification

ParameterStandard
Sample rate48 kHz, 24-bit
Speaker consistencySame booth, mic, distance and time-of-day banding across sessions
ScriptPhonetically balanced, diphone-covering, domain-extended
ProsodyNeutral base set plus optional expressive styles
AlignmentText-audio alignment verified per utterance
SilenceLeading/trailing silence trimmed to a fixed window
Two-speaker conversational recording session in a studio — supporting tts training data for speaker diarisation
Two-speaker conversational recording session in a studio
03

Process

  • Script generation with phoneme and diphone coverage analysis
  • Voice casting with client shortlisting from audition samples
  • Multi-session recording with drift monitoring between sessions
  • Alignment verification and mispronunciation review by a linguist
  • Delivery with a coverage report
04

Metrics this feeds

  • Diarisation error rate
  • Overlap detection recall
  • Speaker-count accuracy
05

Failure modes to design out

  • Overlap edited out during recording
  • Single-channel-only capture leaving no reliable ground truth

Session drift is the main TTS killer. Every session is compared acoustically against the reference session and re-recorded if it drifts.

06

Deliverables

  • Studio WAV per utterance
  • Verified transcripts and pronunciation notes
  • Phoneme coverage report
  • Voice talent licence and consent documentation

Frequently asked

Is tts datasets the right service for speaker diarisation?

It covers per-speaker isolated channels with a mixed reference. Most speaker diarisation 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 tts datasets for speaker diarisation

Send the metric you need to move.

Request a dataset quote