CHiME-9 ECHI: A Machine Learning Challenge for Enhancing Conversations to Address Hearing Impairment
This work presents the task and results of the CHiME-9 challenge for Enhancing Conversations to address Hearing Impairment. The challenge considers the scenario of four-party conversations in a noisy, cafeteria-style environment with interfering speech sources and sound effects. Participants are provided with audio recordings made with Meta Aria glasses and hearing aid microphones, and clean speech samples of the conversation participants. The task is to extract the speech of the conversation partners from the noisy multi-channel recordings with the goal of improving the intelligibility and quality of the speech, evaluated using objective metrics and subjective listening tests. This paper...
| Authors | Robert Sutherland, Thomas Kuebert, Marko Lugger et al. |
|---|---|
| Primary category | cs.CL |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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