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AIモデルライブラリ/inclusionAI/Ming-omni-tts-0.5B
モデル情報

Ming-omni-tts-0.5B

inclusionAI · Ming-omni-tts-0.5B

🌐 Project Page ｜🤗 Hugging Face ｜ 🤖 ModelScope | 🎮 Gradio Demo-zh | 🎮 Gradio Demo-en | 💬 DingTalk(钉钉) Ming-omni-tts is a high-performance unified audio generation model that achieves precise control over speech attributes and enables single-channel synthesis of speech, environmental sounds, and music. Powered by a custom 12.5Hz continuous tokenizer and Patch-by-Patch compression, it delivers competitive inference efficiency (3.1Hz). Additionally, the model features robust text normalization capabilities for the accurate and natural narration of complex mathematical and chemical expressions. - 🔊 **Fine-grained Vocal Control:** The model supports precise control over speech rate, pitch, volume, emotion, and dialect through simple commands. Notably, its accuracy for Cantonese dialect control is as high as **93%**, and its emotion control accuracy reaches **46.7%**, surpassing CosyVoice3. - 🌌 **Intelligent Voice Design:** Features 100+ premium built-in voices and supports zero-shot voice design through natural language descriptions. Its performance on the Instruct-TTS-Eval-zh benchmark is on par with Qwen3-TTS. - 🎶 **Immersive Unified Generation:** The industry’s first autoregressive model to jointly generate speech, ambient sound, and music in a single channel. Built on a custom 12.5Hz continuous tokenizer and a DiT head architecture, it delivers a seamless, "in-the-scene" auditory experience. - ⚡ **High-efficiency Inference:** Introduces a "Patch-by-Patch" compression strategy that reduces the LLM inference frame rate to 3.1Hz. This significantly cuts latency and enables podcast-style audio generation while preserving naturalness and audio detail. - 🧪 **Professional Text Normalization:** The model accurately parses and narrates complex formats, including mathematical expressions and chemical equations, ensuring natural-sounding output for specialized applications.

翻訳待ちのため原文を表示しています。

音声合成license:apache-2.0
コンテキスト長非公開
入力 → 出力テキスト → 音声
モデルウェイト未確認
情報更新日時2026/11/2 19:16:34
OVERVIEW

モデル紹介

🌐 Project Page ｜🤗 Hugging Face ｜ 🤖 ModelScope | 🎮 Gradio Demo-zh | 🎮 Gradio Demo-en | 💬 DingTalk(钉钉) Ming-omni-tts is a high-performance unified audio generation model that achieves precise control over speech attributes and enables single-channel synthesis of speech, environmental sounds, and music. Powered by a custom 12.5Hz continuous tokenizer and Patch-by-Patch compression, it delivers competitive inference efficiency (3.1Hz). Additionally, the model features robust text normalization capabilities for the accurate and natural narration of complex mathematical and chemical expressions. - 🔊 **Fine-grained Vocal Control:** The model supports precise control over speech rate, pitch, volume, emotion, and dialect through simple commands. Notably, its accuracy for Cantonese dialect control is as high as **93%**, and its emotion control accuracy reaches **46.7%**, surpassing CosyVoice3. - 🌌 **Intelligent Voice Design:** Features 100+ premium built-in voices and supports zero-shot voice design through natural language descriptions. Its performance on the Instruct-TTS-Eval-zh benchmark is on par with Qwen3-TTS. - 🎶 **Immersive Unified Generation:** The industry’s first autoregressive model to jointly generate speech, ambient sound, and music in a single channel. Built on a custom 12.5Hz continuous tokenizer and a DiT head architecture, it delivers a seamless, "in-the-scene" auditory experience. - ⚡ **High-efficiency Inference:** Introduces a "Patch-by-Patch" compression strategy that reduces the LLM inference frame rate to 3.1Hz. This significantly cuts latency and enables podcast-style audio generation while preserving naturalness and audio detail. - 🧪 **Professional Text Normalization:** The model accurately parses and narrates complex formats, including mathematical expressions and chemical equations, ensuring natural-sounding output for specialized applications.

主な特徴

特点摘要待依据来源补齐，不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

PRICING & COST

出典別料金と費用分析

料金はチャネル・地域・設定によって異なります。各チャネルの料金は個別に表示し、提供元の統一公式料金とは見なしません。

出典・チャネル入力出力課金単位収集日時
確認可能な料金がありません。出典を確認してください。

月額の基本トークン費用を試算

—

試算はキャッシュ割引、段階料金、マルチモーダル追加料金、検索、税金、追加推論出力を含みません。

INDEPENDENT BENCHMARKS

公開評価と実行設定

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

収録済みの全ランキング →

よくある質問

オープンウェイトなら無料で商用利用できますか？

必ずしもそうではありません。バージョン別のライセンス、商用条件、利用方針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。

これはリアルタイムの請求料金ですか？

収集日時付きの料金スナップショットです。最新のバージョン、地域、割引、課金方式は各チャネルで確認してください。

出典と追跡記録

huggingface · inclusionAI/Ming-omni-tts-0.5B ↗2026/11/1 19:18:37
huggingface · enrich:c6b90607-ec25-46f6-a4eb-1290a5829ca5 ↗2026/10/29 22:31:49

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。