Honk：用于关键词识别的卷积神经网络的PyTorch再实现
Honk: A PyTorch Reimplementation of Convolutional Neural Networks for Keyword Spotting
摘要：
我们描述了Honk，这是一个开源的PyTorch重新实现的卷积神经网络，用于TensorFlow中包含的关键字识别。这些模型对于识别基于语音的接口中的“命令触发”是有用的（例如，“Hey Siri”），其充当用于话语的音频记录的显式提示，所述音频记录被发送到云以进行完全语音识别。对Google最近发布的Speech Commands Dataset的评估表明，我们的重新实现在准确性方面具有可比性，并为关键字定位任务的未来工作提供了一个起点。
英文摘要：
We describe Honk, an open-source PyTorch reimplementation of convolutional neural networks for keyword spotting that are included as examples in TensorFlow. These models are useful for recognizing "command triggers" in speech-based interfaces (e.g., "Hey Siri"), which serve as explicit cues for audio recordings of utterances that are sent to the cloud for full speech recognition. Evaluation on Google's recently released Speech Commands Dataset shows that our reimplementation is comparable in accuracy and provides a starting point for future work on the keyword spotting task.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
