PolySpeech-100: A Large-Scale Benchmark for Speech Understanding Across 100+ Languages and Dialects
arXiv:2606.01016v1 Announce Type: new Abstract: While End-to-End (E2E) Speech-Large Language Models (Speech-LLMs) are rapidly evolving, their evaluation methodologies remain limited to the era of simple transcription. Existing benchmarks suffer from three critical limitations: a pronounced bias towards high-resource languages, a focus on low-level recognition (ASR) rather than semantic reasoning, and a neglect of regional dialects. To bridge this gap, we introduce PolySpeech-100, a massive-scale benchmark designed to assess `native-level' speech comprehension across 110 linguistic variants. We
The development of PolySpeech-100 is a direct response to the limitations of current End-to-End Speech-Large Language Models (Speech-LLMs) evaluation, which has lagged behind the rapid advancements in the models themselves.
This benchmark addresses critical biases in existing speech understanding evaluations, fostering the development of Speech-LLMs that are genuinely capable of 'native-level' comprehension across a vast array of global languages and dialects.
The focus of speech AI evaluation will shift from low-level transcription (ASR) to more complex semantic reasoning and inclusive linguistic understanding, pushing models towards broader applicability.
- · AI researchers in speech recognition and NLP
- · Speech-LLM developers
- · Users of diverse, low-resource languages
- · Multilingual content platforms
- · Models biased towards high-resource languages
- · Legacy ASR-focused evaluation methodologies
PolySpeech-100 will accelerate the training of more robust and unbiased multilingual Speech-LLMs.
Improved Speech-LLMs will enable AI applications to serve a significantly wider global audience with higher accuracy and nuance, reducing digital language barriers.
The enhanced accessibility of AI through multilingual speech understanding could contribute to a more equitable distribution of AI benefits and potentially inform sovereign AI development in non-English speaking nations.
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