Alexander Lerch
Publications106
Citations357
Highly Influential Citations33
- Publications
- Influence
- Alexander Lerch
- 2012
With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems.… (More)
The design, implementation, and evaluation of a system for automatic audio signal classification is presented. The signals are classified according to audio type, differentiating between three speech… (More)
- Chih-Wei Wu, Alexander Lerch
- 23rd European Signal Processing Conference…
- 2015
In this paper, a drum transcription algorithm using partially fixed non-negative matrix factorization is presented. The proposed method allows users to identify percussive events in complex mixtures… (More)
Abstract Audio-to-audio alignment is the task of synchronizing two audio sequences with similar musical content in time. We investigated a large set of audio features for this task. The features were… (More)
- Alexander Lerch
- ISMIR
- 2006
The deviation of the tuning frequency from the standard tuning frequency 440Hz is evaluated for a database of classical music. It is discussed if and under what circumstances such a deviation may… (More)
- Chih-Wei Wu, Christian Dittmar, +5 authors Alexander Lerch
- IEEE/ACM Transactions on Audio, Speech, and…
- 2018
In Western popular music, drums and percussion are an important means to emphasize and shape the rhythm, often defining the musical style. If computers were able to analyze the drum part in recorded… (More)
Instrument recognition as a task in MIR is largely data driven. This drives a need for large datasets that cater to the need of these algorithms. Several datasets exist for the task of instrument… (More)
- Xinquan Zhou, Alexander Lerch
- ISMIR
- 2015
In this paper, we utilize deep learning to learn high-level features for audio chord detection. The learned features, obtained by a deep network in bottleneck architecture, give promising results and… (More)
This paper presents FEAPI, an easy-to-use platform-independent plugin application programming interface (API) for the extraction of low level features from audio in PCM format in the context of music… (More)
- Udit Gupta, Elliot Moore, Alexander Lerch
- IEEE Workshop on Applications of Signal…
- 2015
Singing Voice Separation (SVS) is a task which uses audio source separation methods to isolate the vocal component from the background accompaniment for a song mix. This paper discusses the methods… (More)