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Hugging Face benchmarks ASR for bilingual customer voice agents

Hugging Face has developed a benchmark to evaluate how well automatic speech recognition (ASR) systems handle code-switched speech, where individuals switch between languages mid-sentence. This is crucial for voice agents serving bilingual customer bases. The benchmark, covering language pairs like Spanish-English and French-English, uses HR and IT service management scenarios. Top-performing models identified include ElevenLabs Scribe V2, Gemini 3 Flash, and Assembly AI Universal 3-Pro, with results reported using Word Error Rate (WER), Semantic Word Error Rate (SWER), and Answer Error Rate (AER). AI

IMPACT Sets a new standard for evaluating voice agents in multilingual enterprise environments, potentially driving improvements in ASR for global customer service.

RANK_REASON The cluster describes a new benchmark and dataset for evaluating ASR systems on code-switched speech, along with performance results for several models.

Read on Hugging Face Blog →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Hugging Face benchmarks ASR for bilingual customer voice agents

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The cluster describes a new benchmark and dataset for evaluating ASR systems on code-switched speech, along with performance results for several models.
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COVERAGE [2]

  1. Hugging Face Blog TIER_1 English(EN) ·

    Can Voice Agents Handle Bilingual Customers? Benchmarking Frontier ASR on Code-Switched Speech

  2. Mastodon — fosstodon.org TIER_1 日本語(JA) · [email protected] ·

    Can Voice Agents Handle Bilingual Customers? Benchmark Evaluation of Frontier ASR on Code-Switching Speech https:// huggingface.co/blog/ServiceNow -AI/code-switching ※AI-generated auto-post (headline + link) # AI # Generative AI # LL

    【音声エージェントはバイリンガルの顧客に対応できるか?コードスイッチング音声におけるFrontier ASRのベンチマーク評価】 https:// huggingface.co/blog/ServiceNow -AI/code-switching ※AI生成の自動投稿(見出し+リンク) # AI # 生成AI # LLM # AIGenerated