Speaker Diarisation: Challenges and Solutions in Datasets One of the most critical yet often overlooked tasks is diarisation. When audio data contains multiple speakers, and sometimes in multiple languages that require code-switching, it is not enough to transcribe the words alone. Understanding who spoke when is equally important, particularly for industries where speaker roles, dialogue context, and accurate segmentation directly affect the value of the data. This is where diarisation comes into play. Speaker diarisation, sometimes called audio diarisation or multi-speaker voice tagging, is the process of partitioning an audio stream into segments according to the identity of the speaker. It answers two fundamental questions: Which speaker is speaking? When did they speak? #speakerdiarisation #diarisation #datasets https://lnkd.in/dc5ScAmh
Understanding Speaker Diarisation: Challenges and Solutions
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Speaker Diarisation: Challenges and Solutions in Datasets One of the most critical yet often overlooked tasks is diarisation. When audio data contains multiple speakers, and sometimes in multiple languages that require code-switching, it is not enough to transcribe the words alone. Understanding who spoke when is equally important, particularly for industries where speaker roles, dialogue context, and accurate segmentation directly affect the value of the data. This is where diarisation comes into play. Speaker diarisation, sometimes called audio diarisation or multi-speaker voice tagging, is the process of partitioning an audio stream into segments according to the identity of the speaker. It answers two fundamental questions: Which speaker is speaking? When did they speak? #speakerdiarisation #diarisation #datasets https://lnkd.in/dYjig-Ss
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Experienced Marketing Leader | Passionate Product Leader | Customer and Employee Experience Expert
Accuracy across accents is so important, especially when those transcripts are used for AI-generated call summaries, real-time sentiment analysis, and org-wide trend analysis. Don't settle for inaccuracies!
🚨 Independent Benchmarking: Speech-to-Text Accuracy The Tolly Group evaluated the speech-to-text accuracy of 8x8’s built-in transcription engine versus comparable services from Dialpad and RingCentral. 🔍 Test scope: 15 English-language audio files (3–7 min each) on customer-support topics Controlled loop-back playback, repeated 4x per platform Accuracy measured by word-error-rate (WER) via the open-source jiwer library 📊 Key Findings: Best-case WER (lower is better): • 8x8 → 3.43% • Dialpad → 8.03% • RingCentral → 8.08% Average WER (all runs): • 8x8 → 4.54% • Dialpad → 8.53% • RingCentral → 9.20% Transcript availability: • 8x8 → ~50s after call • Dialpad & RingCentral → Near real-time (but less accurate) 🌍 Accent handling: All systems showed higher error rates for Scottish and Welsh speakers, but 8x8 consistently delivered better performance across accents. ✅ Bottom line: 8x8 delivers more than 2x better accuracy than its competitors, proving that reliable transcripts matter more than near-instant—but error-prone—captions. https://lnkd.in/eHq94WxS #8x8 #AITranscription
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Accuracy across accents is so important, especially when those transcripts are used for AI-generated call summaries, real-time sentiment analysis, and org-wide trend analysis. Don't settle for inaccuracies!
🚨 Independent Benchmarking: Speech-to-Text Accuracy The Tolly Group evaluated the speech-to-text accuracy of 8x8’s built-in transcription engine versus comparable services from Dialpad and RingCentral. 🔍 Test scope: 15 English-language audio files (3–7 min each) on customer-support topics Controlled loop-back playback, repeated 4x per platform Accuracy measured by word-error-rate (WER) via the open-source jiwer library 📊 Key Findings: Best-case WER (lower is better): • 8x8 → 3.43% • Dialpad → 8.03% • RingCentral → 8.08% Average WER (all runs): • 8x8 → 4.54% • Dialpad → 8.53% • RingCentral → 9.20% Transcript availability: • 8x8 → ~50s after call • Dialpad & RingCentral → Near real-time (but less accurate) 🌍 Accent handling: All systems showed higher error rates for Scottish and Welsh speakers, but 8x8 consistently delivered better performance across accents. ✅ Bottom line: 8x8 delivers more than 2x better accuracy than its competitors, proving that reliable transcripts matter more than near-instant—but error-prone—captions. https://lnkd.in/eHq94WxS #8x8 #AITranscription
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Accuracy across accents is so important, especially when those transcripts are used for AI-generated call summaries, real-time sentiment analysis, and org-wide trend analysis. Don't settle for inaccuracies!
🚨 Independent Benchmarking: Speech-to-Text Accuracy The Tolly Group evaluated the speech-to-text accuracy of 8x8’s built-in transcription engine versus comparable services from Dialpad and RingCentral. 🔍 Test scope: 15 English-language audio files (3–7 min each) on customer-support topics Controlled loop-back playback, repeated 4x per platform Accuracy measured by word-error-rate (WER) via the open-source jiwer library 📊 Key Findings: Best-case WER (lower is better): • 8x8 → 3.43% • Dialpad → 8.03% • RingCentral → 8.08% Average WER (all runs): • 8x8 → 4.54% • Dialpad → 8.53% • RingCentral → 9.20% Transcript availability: • 8x8 → ~50s after call • Dialpad & RingCentral → Near real-time (but less accurate) 🌍 Accent handling: All systems showed higher error rates for Scottish and Welsh speakers, but 8x8 consistently delivered better performance across accents. ✅ Bottom line: 8x8 delivers more than 2x better accuracy than its competitors, proving that reliable transcripts matter more than near-instant—but error-prone—captions. https://lnkd.in/eHq94WxS #8x8 #AITranscription
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At SAI, our simultaneous interpretation solution lets interpreters translate spoken messages in real time while the speaker is still talking so your event flows naturally, without long pauses or interruptions. We deploy: Sound‑proof booths or portable interpreting stations Headsets, receivers, and audio transmission systems Teams of expert interpreters who rotate frequently to maintain accuracy and clarity. The result? Attendees receive the message in their own language at the same moment it’s spoken making your meeting inclusive, seamless, and powerful. . Curious how this looks in practice? Reach out and we’ll show you! https://sailanguage.com/ . . . . #SimultaneousInterpretation #RealTimeTranslation #LanguageAccess #InclusiveEvents #SAIInterpretation #InterpretWithImpact #GlobalCommunication #BridgeTheGap #HearEveryVoice
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Two-page cheat sheet for audio quality assessment. Quick reference covering: → 10 common artifacts with detection tips → Rating scale & decision tree → Key metrics & standards Part of a complete guide series (see previous posts for full versions). #AudioAI #MachineLearning #CheatSheet
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Hours of audio evidence can overwhelm even the best teams. Rewinding, replaying, and piecing together details slows investigations down. In our latest blog, we share how investigators can transform recordings into searchable text, uncover hidden connections, and move from raw audio to actionable leads faster. Read the full post: https://lnkd.in/gpBrR63w #DigitalIntelligence #Investigations #Transcription
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Running late and need to proofread a 📄 document? With ✨ Gemini ✨ in #GoogleDocs, you can generate an 🔊 audio version of a document and hear it be 📖 read aloud to you, letting you 🎧 listen to the document whilst you’re on the go. You’ll have the ability to adjust the ⏯️ playback speed and select a 🗣️ voice that suits you. Learn how: https://lnkd.in/e_iH6hbJ #GoogleWorkspace #Gemini
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Time to hit that solo! 🎧 In this week’s #TuesdayTutorial, Richard Evans breaks down how to use the solo function in Viz Connect Audio to isolate input channels and route straight to your headphones. Making it easy to fine-tune your mix or focus on the feed that matters most. Keep up with all of Richard’s tutorials, here ▶️ https://ow.ly/E3fz50XfGuL #AudioProduction #VizConnectAudio #Vizrt
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New Tuesday Tutorial focusing on how to use the SOLO function on the Viz Connect Audio which transforms analog audio sources into NDI audio to share across your network without tons of cable runs and gaffe tape. check-a-check it out :)
Time to hit that solo! 🎧 In this week’s #TuesdayTutorial, Richard Evans breaks down how to use the solo function in Viz Connect Audio to isolate input channels and route straight to your headphones. Making it easy to fine-tune your mix or focus on the feed that matters most. Keep up with all of Richard’s tutorials, here ▶️ https://ow.ly/E3fz50XfGuL #AudioProduction #VizConnectAudio #Vizrt
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