We propose a model to estimate the fundamental frequency in monophonic audio, often
referred to as pitch estimation. We acknowledge the fact that obtaining ground truth …

The past decade has witnessed a growing interest in deploying automatic speech
recognition (ASR) in communication networks. The networks such as wireless networks …

Automatic singing transcription (AST), which refers to the process of inferring the onset,
offset, and pitch from the singing audio, is of great significance in music information retrieval …

This work proposes a Deep neural network (DNN) based method for reconstructing speech
magnitude spectrum from Mel‐frequency cepstral coefficients (MFCCs). We train a DNN …

As one of the fundamental tasks in music and speech signal processing, pitch tracking has
been attracting attention for decades. While a human can focus on the voiced pitch even in …

The frame rate of the observation sequence in distributed speech recognition applications
may be reduced to suit a resource-limited front-end device. In order to use models trained …

Pitch estimation is widely used in speech and audio signal processing. However, the current
methods of modeling harmonic structure used for pitch estimation cannot always match the …

We present a method to estimate the fundamental frequency in monophonic audio, often
referred to as pitch estimation. In contrast to existing methods, our neural network can be …

Most existing duration modeling approaches facilitates phone recognizer and require
manually annotated corpus to train the segmentation models, which is usually cost-and time …

The desire for improved user interfaces for distributed speech and multimodal services on
mobile devices has motivated the need for reliable recognition performance over mobile …