Hume AI 发布 Hume Decision API，用音频原生模型回答录音问题
Hume AI has launched a new Hume Decision API, an audio-native model that can answer questions about a recording by analyzing the audio itself.
Hume AI 推出 Hume Decision API，这是一个音频原生模型，可直接分析录音本身来回答关于录音的问题。用户可以自定义问题和选项，例如判断来电者是否显得沮丧，并获得对人类听众会如何作答的估计。初步测试中，该模型与评审组平均答案的一致率为 70.7%，单个人类听众为 56.5%。
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 1000 万+ 人类判断训练，因此它的回答方式与人类听众一致。 支持实时处理，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
Hume AI has launched a new Hume Decision API, an audio-native model that can answer questions about a recording by analyzing the audio itself.
Users can write their own questions and answer options, such as whether a caller sounds frustrated, and receive an estimate of how human listeners would answer.
In initial tests, the model agreed with the panel's average answer 70.7% of the time, compared to 56.5% for a single listener.