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Open nowPosted 145 days ago

语音模型数据专家（小语种方向）

acnc6zeentra/index41 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now语音模型数据专家（小语种方向）acnc6zeentra/index · Shanghai, Chinese Mainland

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  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 145 days ago

The posting

1.面向下一代语音生成大模型和产品，建设以语音、音效、音乐等音频模态为核心的数据体系，持续扩增高表现力、高质量、高复杂度的源数据； 2.负责千万小时级别训练数据的收集、筛选、构造和治理，覆盖多语言、小语种、方言、口音、说话人、场景、风格、情绪、音效和音乐等维度； 3.搭建高效的音频数据处理 pipeline，包括音视频抽取、转码、切分、VAD、转写、说话人分离、文本对齐、去重、质量筛选、自动化质检和数据分布分析； 4.与算法、训练和评测团队协作，将模型能力目标转化为数据方案，围绕数据质量、多样性和复杂度持续提升模型在自然度、表现力、多语言、方言和复杂音频场景中的能力上限。

1.在语音、音频、语音生成、音乐生成、音频理解、多语言 NLP、多模态或相关领域有扎实的数据工作经验； 2.理解数据是当前大模型能力形成的核心，能够围绕模型目标系统性规划数据来源、数据构造、质量治理和迭代闭环； 3.具备千万小时级别或超大规模音频训练数据的处理意识和经验，熟悉大规模数据采集、清洗、筛选、质检、入库和版本管理； 4.熟悉多语言、小语种、方言或口音数据处理，理解低资源数据中的噪声、稀缺性、转写不一致、文本规范化和质量控制问题； 5.熟悉方言相关文本前端建设，包括文本规范化、方言词表、读音规则、多音字处理、口语化表达、拼音/注音/音素映射等； 6.熟悉语音、音效、音乐等音频模态的数据筛选和构造方法，能够从质量、多样性和复杂度三个维度评估数据价值； 7.具备数据平台和数据链路意识，理解 schema、元数据、标签体系、数据 lineage、训练/评测隔离、实验追踪和可追溯性的重要性； 8.熟悉 Python、SQL、Shell、Linux、Git，以及 Ray、Lance、Daft、Spark、DuckDB、Parquet、Arrow、Airflow、Dagster 等大规模并行数据处理或任务编排工具者优先。

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