---
title: Speaker Diarization for Multi-File Oral Histories
seo_title: Speaker Diarization for Multi-File Oral Histories
description: Evaluate oral history using published MOSS results and a practical review
  procedure for selection, validation, and reporting.
topic: Speech Transcription and Diarization
date: '2026-11-14'
lastmod: '2026-11-14'
author: Model Workflow Lab Editorial
author_type: Organization
faq:
- q: Can I merge files by S01?
  a: Map identities independently for each session.
- q: What if the identity is unclear?
  a: Preserve the local tag and flag the unresolved mapping.
- q: Is the metric gap a direct identity accuracy score?
  a: It compares two text error measures under the published protocol.
category: library
copyright: Copyright 2026 ModelWorkflowLab.com; subject to stated permissions and
  exceptions.
---
# Speaker Diarization for Multi-File Oral Histories

## Which diarization model should an oral-history archive evaluate?

MOSS-Transcribe-Diarize 0.9B combines timestamped transcription with anonymous speaker labels. On AISHELL-4 its published CER and cpCER are 14.84% and 15.83%, a difference of 0.99 percentage points. The corresponding differences are 3.59 for VibeVoice ASR and 4.68 for Gemini 3 Pro in that comparison. The difference between two text metrics is distinct from a time-based diarization error rate. [Evaluation table](https://github.com/OpenMOSS/MOSS-Transcribe-Diarize)

![Proposed review workflow: review local labels, verify identities, merge session indexes](/assets/images/speaker-diarization-multi-file-oral-histories.svg)

## A published example and a collection-level test

The official dialogue examples display anonymous labels and time ranges. For a proposed oral-history pilot, use two consented sessions in which the guest speaks first in one file and the interviewer speaks first in the other. Map each file to the approved roster before joining its index. We would listen to a known passage from each participant and flag every unresolved mapping. [Official examples](https://www.moss.cn/models/moss-transcribe-diarize) · [Technical report](https://arxiv.org/abs/2601.01554)

| Review unit | Verify |
|---|---|
| Turn | Words and timestamps against source audio |
| Session | Anonymous tag mapped to the correct participant |
| Collection | Verified identity across recordings |
| Exception | Unresolved identity and supporting time range |

Save the verified mapping separately from raw model output. Report incorrect merges and unmatched turns on your collection. This proposed review addresses cross-file linkage, which the published within-recording score does not quantify. [Checkpoint](https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize)

See [returning speakers](/diarization-returning-speakers-long-meetings/), [overlap tests](/speaker-diarization-overlapping-dialogue/), and [roundtable indexing](/speech-to-text-roundtable-speaker-index/).

## English SEO keywords

oral history, speaker diarization, cross-file speaker mapping.