AI NEWS.ccAI正在发生 未来正在更新
♡ 我的收藏 0
AI 模型库/NVIDIA/magpie_tts_multilingual_357m
MODEL PROFILE · 模型档案

magpie_tts_multilingual_357m

NVIDIA · magpie_tts_multilingual_357m

> [!Note] > July 21, 2026: MagpieTTS v2607 was released with support for 3 new languages (Arabic, Korean, Portuguese). > > For the older checkpoints, refer to below tags: > > - Released on March 2026, v2602. > - Released on January 2026, v2512. MagpieTTS is an end-to-end multilingual neural text-to-speech model that synthesizes speech using 5 English speaker voices — Aria, Jason, Leo, Sofia, and John Van Stan — across 12 languages: Arabic (ar), Chinese (zh), English (en), French (fr), German (de), Hindi (hi), Italian (it), Japanese (ja), Korean (ko), Portuguese (pt), Spanish (es), and Vietnamese (vi). The model adopts a transformer encoder–decoder architecture that autoregressively predicts discrete audio codec tokens, using multi-codebook prediction (typically 8 codebooks) with frame stacking (factor = 2) and a local transformer for fine-grained refinement of high-fidelity audio. To improve robustness and controllability, training incorporates attention priors for stable text-to-audio alignment, classifier-free guidance (CFG) for stronger conditioning, and Group Relative Policy Optimization (GRPO) for preference-aligned generation. At inference time, MagpieTTS supports batched synthesis of complete utterances as well as long-form generation of extended text via a sliding-window mechanism; the predicted codec tokens are then decoded into speech waveforms by a frozen pretrained audio codec model (NanoCodec). This release also removed zero-shot voice-cloning capability for security reasons, and added IPA grapheme-to-phoneme (G2P) support for custom dictionaries and code-switching, and updated G2P support for English-to-Katakana code-switching. MagpieTTS is for developers, researchers, and product teams building multilingual speech applications that need consistent speaker voices across 12 languages. Typical applications include cascade voice agents, audiobook and content narration, accessibility tools, dubbing and localization pipelines, and interactive media. IPA grapheme-to-phoneme (G2P) support for custom dictionaries and code-switching (including English-to-Katakana) also enables mixed-language content and domain-specific pronunciation.

译文排队中，当前展示来源原文。

语音合成license:other
上下文窗口来源未披露
输入 → 输出文本 → 音频
模型权重待核验
档案更新时间2026/11/2 19:17:05
OVERVIEW

模型介绍

> [!Note] > July 21, 2026: MagpieTTS v2607 was released with support for 3 new languages (Arabic, Korean, Portuguese). > > For the older checkpoints, refer to below tags: > > - Released on March 2026, v2602. > - Released on January 2026, v2512. MagpieTTS is an end-to-end multilingual neural text-to-speech model that synthesizes speech using 5 English speaker voices — Aria, Jason, Leo, Sofia, and John Van Stan — across 12 languages: Arabic (ar), Chinese (zh), English (en), French (fr), German (de), Hindi (hi), Italian (it), Japanese (ja), Korean (ko), Portuguese (pt), Spanish (es), and Vietnamese (vi). The model adopts a transformer encoder–decoder architecture that autoregressively predicts discrete audio codec tokens, using multi-codebook prediction (typically 8 codebooks) with frame stacking (factor = 2) and a local transformer for fine-grained refinement of high-fidelity audio. To improve robustness and controllability, training incorporates attention priors for stable text-to-audio alignment, classifier-free guidance (CFG) for stronger conditioning, and Group Relative Policy Optimization (GRPO) for preference-aligned generation. At inference time, MagpieTTS supports batched synthesis of complete utterances as well as long-form generation of extended text via a sliding-window mechanism; the predicted codec tokens are then decoded into speech waveforms by a frozen pretrained audio codec model (NanoCodec). This release also removed zero-shot voice-cloning capability for security reasons, and added IPA grapheme-to-phoneme (G2P) support for custom dictionaries and code-switching, and updated G2P support for English-to-Katakana code-switching. MagpieTTS is for developers, researchers, and product teams building multilingual speech applications that need consistent speaker voices across 12 languages. Typical applications include cascade voice agents, audiobook and content narration, accessibility tools, dubbing and localization pipelines, and interactive media. IPA grapheme-to-phoneme (G2P) support for custom dictionaries and code-switching (including English-to-Katakana) also enables mixed-language content and domain-specific pronunciation.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价，请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

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。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用？

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗？

不是实时结算价格，而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

huggingface · nvidia/magpie_tts_multilingual_357m ↗2026/10/29 16:40:00
huggingface · enrich:f84f18c9-6b54-4b9d-8600-66a216428f12 ↗2026/10/30 04:26:27

许可证：other。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。