Text normalize与streaming E2E模型联合训练优化 Speech recognition engine为了更好的客户体验,一般会在engine解码结束后对top1结果进行text normalize(增加合适的标点符号,阿拉伯数字格式转换以及英文大小写格式转换等处理)。但On-device资源有限,增加额外的text normalize模型会增加额外的内容和计算负担。为了省略text normaliz...
To make our VoiceFilter-Lite model robust to various noise conditions, we add more variations to the noisification process: (1) the interference audio sources can be either speech from other spks, or non-speech noise such as ambient noise or background music; (2) the noises can be applied...
PROBLEM TO BE SOLVED: To provide an onboard speech recognition device capable of preventing degradation of driver's attentiveness, keeping a recognition rate constant and high under any running condition, and satisfying an operator's operation timing sense.SAKIYAMA KAZUHIRO...
On-device Speech Recognition for Apple Silicon. Contribute to modmed/WhisperKit development by creating an account on GitHub.
Java documentation for android.speech.RecognitionSupport.getSupportedOnDeviceLanguages(). Portions of this page are modifications based on work created and shared by the Android Open Source Project and used according to terms described in the Creative Commons 2.5 Attribution License. Applies to პრ...
While current state-of-the-art Automatic Speech Recognition (ASR) systems achieve high accuracy on typical speech, they suffer from significant performance degradation on disordered speech and other atypical speech patterns. Personalization of ASR models, a commonly applied solution to this problem, is...
General Card Recognition Form Recognition Language/Voice-related Services Translation Real-Time Translation On-device Translation Language Detection Real-Time Language Detection On-device Language Detection Automatic Speech Recognition Text to Speech Text to Speech On-device Text to Speech ...
Speech 程序集: Mono.Android.dll C# 复制 [Android.Runtime.Register("setPendingOnDeviceLanguages", "(Ljava/util/List;)Landroid/speech/RecognitionSupport$Builder;", "", ApiSince=33)] public Android.Speech.RecognitionSupport.Builder SetPendingOnDeviceLanguages (System.Collections.Generic.ILis...
We describe a large vocabulary speech recognition system that is accurate, has low latency, and yet has a small enough memory and computational footprint to run faster than real-time on a Nexus 5 Android smartphone. We employ a quantized Long Short-Term Memory (LSTM) acoustic model trained wi...
在流式识别(文中也被称为incremental speech recognition)的过程中,显示出来给用户看的partial results经常会随着说话的过程而产生较大变化,给用户带来不好的体验。本文介绍了一些指标来量化这种流式识别中的不确定性(instability),对不稳定性产生的原因进行了归类,并实验了不同优化方法对模型的影响 指标定义 文章将流...