--- title: Why Isn’t the Speaker Identification Correct in My Transcript? description: Claudio’s Speaker Labels feature revolutionizes transcription by identifying and tagging individual speakers within a transcript. This capability is particularly valuable in multi-speaker settings, en --- [Skip to content](https://support.loomanalytics.com/why-isnt-the-speaker-identification-proper-in-my-transcript#main-content) English Show submenu for translations ![Loom\_Analytics\_Logo\_Transparent.png\]](https://support.loomanalytics.com/hs-fs/hubfs/Loom_Analytics_Logo_Transparent.png?height=40&name=Loom_Analytics_Logo_Transparent.png) Open main navigation Close main navigation - English Show submenu for translations - Loom Analytics Loom Analytics Let's Get Started. What Can I Help You With? - There are no suggestions because the search field is empty. 1. [Loom Analytics Knowledge Base](https://support.loomanalytics.com/?hsLang=en) 2. [Loom Analytics Web: Profiles & Workflows](https://support.loomanalytics.com/loom-analytics-web-profiles-workflows?hsLang=en) # Why Isn’t the Speaker Identification Correct in My Transcript? Loom Analytics' Speaker Labels feature revolutionizes transcription by identifying and tagging individual speakers within a transcript. This capability is particularly valuable in multi-speaker settings, enabling effortless tracking and organization of conversations. Learn how to enable Speaker Identification in Loom Analytics [here.](https://support.loomanalytics.com/speaker-identifications?hsLang=en) While Loom Analytics' speaker identification is highly effective, a few factors may influence its performance. #### Factors Impacting Speaker Identification Accuracy: 1. **Audio Quality** High-quality audio is critical for optimal performance. Poor recording conditions, background noise, or unclear audio may reduce Loom Analytics' ability to distinguish between speakers accurately. 2. **Speaker Similarity** When speakers have very similar voices, such as in tone or pitch, the accuracy of differentiation can decrease. 3. **Audio Duration** Loom Analytics performs best with recordings under one hour. Transcribing longer audio files may result in reduced precision in speaker labelling. 4. **Number of Speakers** Loom Analytics is optimized for conversations involving up to four distinct speakers. In recordings with more than four participants, there is an increased likelihood of multiple speakers being grouped under a single label. **Optimizing Performance** To ensure Loom Analytics delivers the most accurate speaker labels: - Use high-quality recording equipment in a quiet environment. - Limit the number of speakers per audio file to four or fewer. - Break longer audio files into smaller segments where possible. 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