MERaLiON-2-10B-ASR
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MERaLiON-2-10B-GGUF
MERaLiON基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗MERaLiON-2-3B-GGUF
MERaLiON基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗MERaLiON-3-10B
MERaLiON基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗MERaLiON-3-3B-ASR
MERaLiON**MERaLiON-3-ASR** is the speech-recognition line in the MERaLiON-3 generation of Speech-Text Large Language Models, developed by I2R, A\*STAR, Singapore. It is purpose-built for Singapore- and Southeast-Asia-centric ASR, with broad coverage across regional languages, dialects, and natural conversational code-switching. - **Languages:** English (Global and Singapore), Mandarin, Malay, Tamil, Indonesian, Thai, Vietnamese - **Chinese dialects:** Cantonese, Hokkien - **Code-switching:** natural conversational English ↔ {Mandarin, Malay, Tamil, Vietnamese, Cantonese, Hokkien} mixtures, including Singlish **MERaLiON-3-ASR-API** is the hosted production endpoint, tuned for real-time and enterprise transcription workloads.
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View details ↗MERaLiON-OmniVoice-Hokkien-TTS
MERaLiON基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗MERaLiON-SER-v1
MERaLiONYou can experience **speech emotion recognition** by selecting Gender/Speech recognition tab via our interactive Hugging Face Space: Upload an audio clip or record your voice to visualize categorical emotions and dimensional affect trajectories in real time. **MERaLiON-SER-v1** is a multilingual **speech emotion recognition (SER)** model jointly predicting 1. **Categorical emotions** – 7 discrete classes *(Neutral, Happy, Sad, Angry, Surprised, Fearful, Disgusted)*, and 2. **Dimensional affect values** – continuous *(Valence, Arousal, Dominance)*. Valence (0 negative, 1 positive), Arousal (0 calm, 1 active), Dominance (0 weak, 1 strong)
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View details ↗MERaLiON-SpeechEncoder-2
MERaLiONWe introduce **MERaLiON-SpeechEncoder-2**, our next-generation multilingual speech encoder that was pre-trained from scratch on a greatly expanded corpus of **1.4 million hours** of unlabeled audio, with a **strong focus on Southeast Asian (SEA) languages and accents**. As a speech foundation model, it encodes speech into a general-purpose, multilingual acoustic representation that can serve as a high-performance backbone for a wide range of downstream tasks — including automatic speech recognition (ASR), speech translation, speaker and language identification, and emotion recognition. **This model can be finetuned on custom datasets, allowing developers to build speech systems tailored to their specific needs.** Unlike many existing models optimized for high-resource, Western languages, MERaLiON-SpeechEncoder-2 is designed from the ground up to reflect the linguistic diversity and complexity of Southeast Asia. Our training data was curated to contain a substantial amount originating from Singapore and SEA, including 60,000 hours of Singapore-accented speech, with a further 160,000 hours covering Singapore’s official languages Chinese, Malay and Tamil, along with a smaller portion of dialects like Hokkien and Cantonese. SEA data amounts to 200,000 hours, including significant proportions of Malay, Thai, Indonesian, Vietnamese, with smaller amounts of Tagalog, Burmese, Javanese, Sundanese, Khmer and Lao. See below for a regional breakdown of the language coverage of our pre-training data. With only **630M parameters (≈2.5 GB in memory)**, the model is easily deployable on most commercial GPUs, eliminating the need for distributed or large-scale compute setups.
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