Benchmarking Human and Automatic Speech Recognition of Diverse Speech: Initial Results
Humans are often considered to be the best listeners and seen as the upper-bound performance of automatic speech recognition (ASR) systems. We present a preliminary comparison of the performances of state-of-the-art ASR systems and Dutch native listeners on the recognition of "diverse" speech, specifically Dutch child and older adults' speech and Flemish. Google Telephony outperformed the other ASR systems. Importantly, the ASR systems showed similar performance to the listeners, and in specific cases even outperformed them. Slight performance differences between the listeners and ASR systems
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- PossiblePossibly related (embedding) · 57%Introducing Real World VoiceEQ: Measuring the human quality of voice AI →
- FuzzySimilar title/name (fuzzy) · 87%huggingface/speech-to-speech →
“Fuzzy title match (0.94): “Benchmarking Human and Automatic Speech Recognition of Diver” ≈ “huggingface/speech-to-speech””
- LinkedLinked via arxiv author · 85%Ilse Huisman →
“Benchmarking Human and Automatic Speech Recognition of Diverse Speech: Initial Results”
- LinkedLinked via arxiv author · 85%Rares Popa →
“Benchmarking Human and Automatic Speech Recognition of Diverse Speech: Initial Results”
- LinkedLinked via arxiv author · 85%Yuanyuan Zhang →
“Benchmarking Human and Automatic Speech Recognition of Diverse Speech: Initial Results”
- LinkedLinked via arxiv author · 85%Odette Scharenborg →
“Benchmarking Human and Automatic Speech Recognition of Diverse Speech: Initial Results”