SMIIP-NV

开源时间：2025年8月

       在自然语言交流中，情感往往是通过像笑声、哭声、咳嗽声等这类非言语声音来传递的。现有大多数语音合成语料库却缺乏对这类非言语声音的标注信息，因此导致生成此类发声的系统相对稀缺。为填补这一空白，我们构建了SMIIP-NV 语料库—— 这是一个同时标注了情感与非言语声音的语音合成语料库，非言语声音涵盖了笑声、哭声以及咳嗽声。据我们所知，SMIIP-NV是目前规模最大的涵盖非言语声音的开源情感语音语料库。该语料库包含 33 小时语音数据，覆盖 5 种不同情感及 3 类非言语发声，针对非言语部分标注了文本以及精确的时间戳信息。 此外，语料库还针对包含笑声或哭声的语音片段进行了专项标注。为验证本数据集的实用价值，我们采用轻量级大语言模型（LLM），搭建了非言语语音合成任务的基准模型。

In natural language communication, emotions are often conveyed through non-verbal sounds (NVs), such as laughter, crying, and cough. However, most existing text-to-speech (TTS) corpora lack annotations for these non-verbal sounds, leading to a scarcity of systems capable of generating them. To address this gap, we introduce SMIIP-NV, a non-verbal speech synthesis corpus annotated with both emotions and non-verbal sounds, including laughter, crying, and cough. To the best of our knowledge, SMIIP-NV is the largest publicly available open-source expressive speech corpus that includes non-verbal speech. It comprises 33 hours of speech data, covering five distinct emotions and three types of non-verbal sounds, with detailed transcriptions and precise timestamps for each occurrence of non-verbal sounds. Additionally, the corpus provides annotations for speech segments that contain laughter or crying. To demonstrate the utility of this dataset, we establish a baseline for non-verbal speech synthesis by employing a lightweight large language model (LLM).

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License: CC BY-NC-SA 4.0