An effective approach to automatically predict the subjective rating for synthetic speech is to
train on a listening test dataset with human-annotated scores. Although each speech sample …

Measuring quality and intelligibility of a speech signal is usually a critical step in
development of speech processing systems. To enable this, a variety of metrics to measure …

Human judgments obtained through Mean Opinion Scores (MOS) are the most reliable way
to assess the quality of speech signals. However, several recent attempts to automatically …

针对通信语音干扰效果客观评估问题, 提出了基于多测度与多模态融合的2 种评估方法. 首先,
利用端点检测算法以及动态时间弯折算法对受扰语音数据进行预处理. 然后 …

Many audio processing tasks require perceptual assessment. However, the time and
expense of obtaining``gold standard''human judgments limit the availability of such data …

In recent years, deep learning based source separation has achieved impressive results.
Most studies, however, still evaluate separation models on synthetic datasets, while the …

The use of audio and visual modality for speaker localization has been well studied in the
literature by exploiting their complementary characteristics. However, most previous works …

Traditionally, speech quality evaluation relies on subjective assessments or intrusive
methods that require reference signals or additional equipment. However, over recent years …

Measuring the quality of noisy speech signals has been an increasingly important problem
in the field of speech processing as more and more speech-communication and human …

Automatic speech quality assessment is essential for audio researchers, developers, speech
and language pathologists, and system quality engineers. The current state-of-the-art …