The computer vision literature shows that randomly weighted neural networks perform
reasonably as feature extractors. Following this idea, we study how non-trained (randomly …

Singing, the vocal productionof musical tones, is one of the most important elements of
music. Addressing the needs of real-world applications, the study of technologies related to …

In this work, we develop a strategy to automatically evaluate pronunciation of singing. We
apply singing-adapted automatic speech recognizer (ASR) in a two-stage approach for …

The assessment of music performances in most cases takes into account the underlying
musical score being performed. While there have been several automatic approaches for …

Oromotor dysfunction caused by neurological disorders can result in significant speech and
swallowing impairments. Current diagnostic methods to assess oromotor function are …

The data-driven computational research on automatic **gju (also known as Bei**g or
Peking opera) singing evaluation lacks a suitable and comprehensive a cappella singing …

Rhythm is an important aspect of singing in music information retrieval. From the principles
of music theory, note duration is related to the time signature of a song, therefore it provides …

This paper presents an automatic lyrics transcription (ALT) method for music recordings that
leverages the framewise semitone-level sung pitches estimated in a multi-task learning …

Automatic music and audio tagging can help increase the retrieval and re-use possibilities of
many audio databases that remain poorly labeled. In this dissertation, we tackle the task of …

In this paper, we propose an efficient and reproducible deep learning model for musical
onset detection (MOD). We first review the state-of-the-art deep learning models for MOD …