The 2nd MLC-SLM Challenge 2026 Opens Registration with a USD 20,000 Prize Pool

CALIFORNIA, CA, UNITED STATES, April 30, 2026 /EINPresswire.com/ -- The 𝟐𝐧𝐝 𝐌𝐮𝐥𝐭𝐢𝐥𝐢𝐧𝐠𝐮𝐚𝐥 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐩𝐞𝐞𝐜𝐡 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝟐𝟎𝟐𝟔, also known as the 𝐌𝐋𝐂-𝐒𝐋𝐌 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝟐𝟎𝟐𝟔, is now open for registration. This year’s challenge features a 𝐭𝐨𝐭𝐚𝐥 𝐩𝐫𝐢𝐳𝐞 𝐩𝐨𝐨𝐥 𝐨𝐟 𝐔𝐒𝐃 𝟐𝟎,𝟎𝟎𝟎 and invites academic teams, industry teams, and individual researchers to advance Speech Large Language Models for real-world multilingual conversational speech.

The 2nd MLC-SLM Challenge focuses on key capabilities required for next-generation Speech LLMs, including 𝐬𝐩𝐞𝐚𝐤𝐞𝐫 𝐝𝐢𝐚𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧, 𝐬𝐩𝐞𝐞𝐜𝐡 𝐫𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧, 𝐚𝐧𝐝 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐩𝐞𝐞𝐜𝐡 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠. Participants will work with multilingual, multi-speaker conversational speech data designed to reflect real-world dialogue scenarios.

𝟐𝐧𝐝 𝐌𝐋𝐂-𝐒𝐋𝐌 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐨𝐟𝐟𝐞𝐫𝐬:
●𝐅𝐫𝐞𝐞 𝐫𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧
●Free access to a large-scale multilingual conversational speech dataset for registered participants, featuring around 𝟐,𝟏𝟎𝟎 𝐡𝐨𝐮𝐫𝐬 𝐨𝐟 𝐝𝐚𝐭𝐚 𝐚𝐜𝐫𝐨𝐬𝐬 𝟏𝟒 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬
●A total prize pool of 𝐔𝐒𝐃 𝟐𝟎,𝟎𝟎𝟎
Support for both academic and industry teams, as well as individual researchers

Following the success of the first MLC-SLM Challenge, which attracted 78 teams from 13 countries and regions, the 2026 edition introduces a larger and more diverse dataset. The first challenge also received 489 valid leaderboard submissions and 14 technical reports, and 𝐢𝐭𝐬 𝐬𝐮𝐦𝐦𝐚𝐫𝐲 𝐩𝐚𝐩𝐞𝐫 𝐡𝐚𝐬 𝐛𝐞𝐞𝐧 𝐚𝐜𝐜𝐞𝐩𝐭𝐞𝐝 𝐛𝐲 𝐈𝐂𝐀𝐒𝐒𝐏 𝟐𝟎𝟐𝟔.

𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐓𝐚𝐬𝐤𝐬
Participants can join two tracks:
𝐓𝐚𝐬𝐤 𝟏: 𝐌𝐮𝐥𝐭𝐢𝐥𝐢𝐧𝐠𝐮𝐚𝐥 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐩𝐞𝐞𝐜𝐡 𝐃𝐢𝐚𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐑𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧
Participants are required to build systems that can identify who is speaking when and transcribe multilingual conversational speech. During evaluation, no oracle segmentation or speaker labels will be provided, making the task closer to real-world speech processing scenarios.

𝐓𝐚𝐬𝐤 𝟐: 𝐌𝐮𝐥𝐭𝐢𝐥𝐢𝐧𝐠𝐮𝐚𝐥 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐩𝐞𝐞𝐜𝐡 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠
Participants are required to build systems that understand multilingual conversations using both acoustic and semantic information. Evaluation will be based on multiple-choice questions about the full conversation, testing the model’s ability to capture meaning, context, and speaker-level information.

Both pipeline-based systems and end-to-end Speech LLM systems are welcome. External datasets and pretrained models are allowed, as long as they are freely accessible and clearly reported.

𝐃𝐚𝐭𝐚𝐬𝐞𝐭 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬
The challenge dataset contains around 𝟐,𝟏𝟎𝟎 𝐡𝐨𝐮𝐫𝐬 𝐨𝐟 𝐭𝐰𝐨-𝐬𝐩𝐞𝐚𝐤𝐞𝐫 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐩𝐞𝐞𝐜𝐡 𝐚𝐜𝐫𝐨𝐬𝐬 𝟏𝟒 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬, including English, French, German, Italian, Portuguese, Spanish, Japanese, Korean, Russian, Thai, Vietnamese, Tagalog, Urdu, and Turkish.

The dataset also includes diverse regional accents, such as Canadian French, Mexican Spanish, Brazilian Portuguese, British English, American English, Australian English, Indian English, and Philippine English.

This makes the MLC-SLM Challenge a valuable benchmark for researchers working on multilingual ASR, speaker diarization, Speech LLMs, and spoken language understanding.

𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧
Registration is now open. Participation is free, and the dataset will be provided free of charge to registered participants.
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤*: https://forms.gle/jfAZ95abGy4ZiNHo7
𝐌𝐨𝐫𝐞 𝐃𝐞𝐭𝐚𝐢𝐥𝐬: https://www.nexdata.ai/competition/mlc-slm
𝐂𝐨𝐧𝐭𝐚𝐜𝐭 𝐄𝐦𝐚𝐢𝐥: mlc-slmw@nexdata.ai

Join the 2nd MLC-SLM Challenge 2026 and help advance the next generation of multilingual Speech Large Language Models.

MLC-SLM Organizing Committee
NEXDATA TECHNOLOGY INC.
+1 760-410-2223
kris.y@nexdata.ai
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