论文标题
使用语音识别的说话者身份证明
Speaker Identification using Speech Recognition
论文作者
论文摘要
随着电话对话，视频会议和语音消息的增加，音频数据正在日复一日地增加。这项研究提供了一种机制，可以基于音调，振幅，频率等人的语音生物特征特征在音频文件中识别说话者。我们提出了一个无监督的学习模型，该模型可以在其中使用有限的数据集学习语音表示。在这项研究中使用了LibrisPeech数据集，我们能够达到1.8的单词错误率。
The audio data is increasing day by day throughout the globe with the increase of telephonic conversations, video conferences and voice messages. This research provides a mechanism for identifying a speaker in an audio file, based on the human voice biometric features like pitch, amplitude, frequency etc. We proposed an unsupervised learning model where the model can learn speech representation with limited dataset. Librispeech dataset was used in this research and we were able to achieve word error rate of 1.8.
