Exploring Spoken Language Identification Strategies for Automatic Transcription of Multilingual Broadcast and Institutional Speech

• URL: http://arxiv.org/abs/2406.09290v1
• Date: Thu, 13 Jun 2024 16:27:56 GMT
• Title: Exploring Spoken Language Identification Strategies for Automatic Transcription of Multilingual Broadcast and Institutional Speech
• Authors: Martina Valente, Fabio Brugnara, Giovanni Morrone, Enrico Zovato, Leonardo Badino,
• Abstract summary: We propose a cascaded system consisting of speaker diarization and language identification. Results show that the proposed system often achieves lower language classification and language diarization error rates. At the same time does not negatively affect speech recognition on monolingual audio.
• Score: 3.812148920168377
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper addresses spoken language identification (SLI) and speech recognition of multilingual broadcast and institutional speech, real application scenarios that have been rarely addressed in the SLI literature. Observing that in these domains language changes are mostly associated with speaker changes, we propose a cascaded system consisting of speaker diarization and language identification and compare it with more traditional language identification and language diarization systems. Results show that the proposed system often achieves lower language classification and language diarization error rates (up to 10% relative language diarization error reduction and 60% relative language confusion reduction) and leads to lower WERs on multilingual test sets (more than 8% relative WER reduction), while at the same time does not negatively affect speech recognition on monolingual audio (with an absolute WER increase between 0.1% and 0.7% w.r.t. monolingual ASR).

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