Update README.md

README.md

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-We 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.
+We 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. See below for a full breakdown of the language coverage of our pre-training data. **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 full breakdown of the language coverage of our pre-training data.
 
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 ## Model Highlights
 
-### Small model size
+#### Small model size
 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.
 
-### Natively multilingual
+#### Natively multilingual
 Building on [MERaLiON-SpeechEncoder-v1](https://huggingface.co/MERaLiON/MERaLiON-SpeechEncoder-v1) (which focused on English and Singlish), this version expands to include English, Chinese, Malay, Tamil, Thai, Indonesian, and Vietnamese, along with codeswitching support across these languages. Given the wide coverage of languages in the training corpus, it may also be applicable beyond the officially supported languages.
   
-### Competitive performance on downstream speech tasks
+#### Competitive performance on downstream speech tasks
 The model retains near state-of-the-art results on the SUPERB benchmark for English, and showcases strong multilingual capabilities deomnstrated through its integration into a [high-performance ASR system shown below](#Automatic-Speech-Recognition-(ASR)).
 
-### Innovative pre-training techniques
+#### Innovative pre-training techniques
 MERaLiON-SpeechEncoder-2 was trained from scratch with an novel extension of the BEST-RQ self-supervised objective, by using more informative latent targets. We also adopted the Muon optimizer, which has previously only been shown to outperform the popular AdamW for LLM training. We find its advantages also carry over to speech-based models. 
  
 ## Model Summary