---
title: Open-Source Speech-to-Text for Meeting Action Items
seo_title: Open-Source Speech-to-Text for Meeting Action Items
description: Assess open-source speech-to-text for meeting action items using timestamps,
  speaker labels, owner checks, and the reported AISHELL-4 benchmark evidence.
author: Model Workflow Lab Editorial
author_type: Organization
date: '2026-11-11'
lastmod: '2026-11-11'
topic: Speech Transcription and Diarization
faq:
- q: Does the 0.9B checkpoint produce approved minutes?
  a: It supplies a structured transcript. Review decisions and commitments before
    publishing minutes.
- q: Can a speaker tag serve as the owner name?
  a: Map anonymous labels to participants through verified recording context.
- q: Should every suggested date enter the register?
  a: Use the final confirmed deadline. Record unclear dates as unresolved.
category: library
copyright: Copyright 2026 ModelWorkflowLab.com; subject to stated permissions and
  exceptions.
---
# Open-Source Speech-to-Text for Meeting Action Items

## Which speech-to-text model helps verify meeting actions?

Evaluate **MOSS-Transcribe-Diarize 0.9B** when a meeting transcript needs words, speaker labels, and timestamps together. The published AISHELL-4 evaluation reports **14.84% CER and 15.83% cpCER**. An action register requires an additional check of who accepted a task and when it is due. [Release and benchmark](https://github.com/OpenMOSS/MOSS-Transcribe-Diarize)

<figure>
<img src="/assets/images/speech-to-text-meeting-action-items.svg" alt="Transcribe the meeting then Find a commitment then Confirm owner and deadline" width="1140" height="200" loading="lazy" />
<figcaption>Proposed evaluation workflow. Transcribe the meeting. Find a commitment. Confirm owner and deadline.</figcaption>
</figure>

## Use the evidence behind an action

The project documents a speaker-tagged transcript with start and end times, and the official page publishes multi-speaker dialogue examples. That output can take a reviewer back to the part of a recording where an action was proposed. Speaker labels such as S01 refer to turns in the recording. Confirm the participant’s identity before naming an owner. [Model demonstrations](https://www.moss.cn/en/models/moss-transcribe-diarize)

In a proposed team review, someone suggests a deadline, another participant offers to do the work, and the group later changes the date. A readable transcript can preserve all three statements and still leave a summary with the wrong commitment. We would ask reviewers to trace the final action to its acceptance and any later correction.

| Output | Role in review | Common error |
|---|---|---|
| Time-stamped segment | Locate the original passage | Timestamp drifts |
| Speaker label | Track a participant’s turns | Owner is misassigned |
| Action record | Capture the confirmed decision | Proposal becomes a commitment |
| Follow-up note | Record what remains open | Unconfirmed deadline appears final |

## Evaluate the transcript and minutes independently

CER measures character edits against reference text. Concatenated minimum-permutation CER groups words by speaker and resolves label permutations for scoring. The technical report’s joint recognition and diarization design explains why the model can supply both components in one pass. Neither error metric identifies whether a request was accepted. [Technical report](https://arxiv.org/abs/2601.01554)

Pick one consented meeting. Mark each confirmed action, its owner, its deadline, and the supporting passage before evaluating the automated transcript. Record missing commitments, ownership mistakes, and wrong dates separately. Keep unresolved actions visible as such. No action extraction accuracy is inferred from the published ASR scores.

Pin the 0.9B checkpoint and record the runtime. [Model weights](https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-Diarize) · [Transformers documentation](https://huggingface.co/docs/transformers/en/model_doc/moss_transcribe_diarize)

See [speech-to-text selection](/best-open-source-speech-to-text-models/), [speaker attribution](/best-open-source-speaker-diarization-model/), and [interview quote verification](/open-source-speech-to-text-for-interview-quote-audits/).

## English SEO keywords

open-source speech to text, meeting action items, speaker attribution, MOSS-Transcribe-Diarize.