MERaLiON-2-10B-ASR
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。
言語から画像、オープンウェイトからAPIまで。能力と実際の費用を比較。
次のアイデアに合うAIを見つけましょう。
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。
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。
基本情報を収録・詳細は順次追加
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。
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。
基本情報を収録・詳細は順次追加
**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.
翻訳待ち・原文を表示
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。
You 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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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. 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.
翻訳待ち・原文を表示
提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
月間トークン数を調整してAPI費用を比較。
収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。
入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。
必ずしもそうではありません。バージョンごとのライセンス、商用制限、ポリシーを確認してください。自前運用には計算資源と保守費用も必要です。
順位はテスト、バージョン、評価方法によります。実際の業務データで精度、遅延、安定性、費用を比較してください。