Hume 推出 Audio Decision API，直接从音频回答情绪与说话人问题
A lot of the meaning in speech sits in the delivery, and models can now be asked about it directly.
Hume AI 发布 Audio Decision API，可直接针对音频片段回答问题，无需先转写，并为每个自定义答案返回概率。该 API 把叹气、笑声、犹豫、重叠说话和背景声纳入模型输入，可实时处理或分析数小时录音，官方称过去需要 10 多个模型完成的工作现在一次调用即可。Rohan Paul 转述称，可提问“这位来电者是否生气”并得到带置信度的直接答案，讽刺语气也不会被误判为正面情绪。
查看原帖隆重推出 Hume Audio Decision API。 想问什么都可以：有多少位说话人？有人在笑吗？来电者是否感到沮丧？ 过去需要 10 多个模型才能完成的工作，现在只需一次调用。 基于超过 1000 万条人类判断训练，因此它的回答方式与人类听众一致。 可实时处理，也可分析长达数小时的录音。 请在下方申请访问权限。
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Introducing the Hume Audio Decision API. Ask anything: How many speakers? Is anyone laughing? Is the caller frustrated? What used to take 10+ models is now one call. Trained on 10M+ human judgments, so it answers the way human listeners would. Realtime, or across hours of recordings. Request access below.
正文
A lot of the meaning in speech sits in the delivery, and models can now be asked about it directly.
The Hume Audio Decision API answers questions about a clip from the audio itself, with no transcript step, and returns a probability for each answer you define.
> puts sighs, laughter, hesitation, overlapping speech and background sounds inside the model’s input. A transcript would have reduced all of them to the same words.
> so you can ask like “Is this caller angry?”, and get a direct answer with a confidence percentage.
> Most AI judges calls by reading a text transcript, which loses tone; But this one listens to the voice itself, so a sarcastic “Oh, perfect” no longer counts as happy.
https://t.co/tewKHPdjY3