Why Kolabtree
Getting started is quick and easy. No upfront fees
It’s free to request a service and invite bids from experts
Discuss requirements with the expert in detail before accepting statement of work from Kolabtree
Collaborate with the expert directly to get your work done the right way
Fund project when you hire the expert, but approve the deliverables only once work is done
Want to hire this expert for a project? Request a quote for free.
Profile Details
Create Project
Hire Dr. Peter G.

Audio DSP, Data Science and Music AI researcher and algorithm developer

Profile Summary
Subject Matter Expertise
Research Feasibility Study, Gray Literature Search, Systematic Literature Review, Secondary Data Collection
Consulting Scientific and Technical Consulting
Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-Non ML, Data Processing
Product Development Formulation
Work Experience

Huawei European Research Institute

- Present


PhD Computer Science

Saarland University and MPI Informatik

April 2008 - November 2012

  • Certification details not provided.
(2019). Audio signal processing stage, audio signal processing apparatus, audio signal processing method, and computer-readable storage medium.
(2018). Audio Signal Processing Apparatus and Method.
(2018). Sound Signal Processing Apparatus and Method for Enhancing a Sound Signal.
(2018). Adaptive Reverberation Cancellation System.
(2018). Audio Signal Processing Apparatus And Method For Processing An Input Audio Signal.
(2018). Digital compressor for compressing an audio signal.
(2018). Audio signal processing apparatus.
(2018). Apparatus and method for estimating an overall mixing time based on at least a first pair of room impulse responses, as well as corresponding computer program.
(2018). Apparatus and method for driving an array of loudspeakers with drive signals.
(2018). Method and mobile device for processing an audio signal.
(2018). Audio signal processing apparatus for processing an input earpiece audio signal upon the basis of a microphone audio signal.
(2018). Apparatus and method for driving an array of loudspeakers.
(2018). Apparatus and method for enhancing a spatial perception of an audio signal.
(2017). Audio signal processing device and method for reproducing a binaural signal.
Geiger, Juergen and Grosche, Peter(2017). Audio signal processing apparatus and method for modifying a stereo image of a stereo signal.
(2017). Signal processing apparatus for enhancing a voice component within a multi-channel audio signal.
(2017). Apparatus and a method for manipulating an input audio signal.
(2016). Audio Compression System for Compressing an Audio Signal.
(2016). System and method for evaluating an acoustic transfer function.
(2016). Apparatus and method for improving a perception of a sound signal.
(2016). Apparatus and Method for Compressing a Set of N Binaural Room Impulse Responses.
(2004). Recreational vehicle bumper device.
(2018). Time-Frequency Masking Strategies for Single-Channel Low-Latency Speech Enhancement Using Neural Networks. 2018 16th International Workshop on Acoustic Signal Enhancement (IWAENC). p. 51--55.
(2018). Perceptually motivated analysis of numerically simulated head-related transfer functions generated by various 3D surface scanning systems. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). p. 551--555.
(2016). Extraction of anthropometric measures from 3d-meshes for the individualization of head-related transfer functions. Audio Engineering Society Convention 140.
(2015). DIALOGUE ENHANCEMENT OF STEREO SOUND. European Signal Processing Conference (EUSIPCO 2015).
(2014). On-line NMF-based Stereo Up-Mixing of Speech Improves Perceived Reduction of Non-Stationary Noise. Audio Engineering Society Conference: 53rd International Conference: Semantic Audio.
(2012). Toward musically-motivated audio fingerprints. 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). p. 93--96.
(2012). Unsupervised detection of music boundaries by time series structure features. Twenty-Sixth AAAI Conference on Artificial Intelligence.
M{\"u}ller, Meinard and Grosche, Peter(2012). Automated segmentation of folk song field recordings. Speech Communication; 10. ITG Symposium. p. 1--4.
(2012). Audio content-based music retrieval. Dagstuhl Follow-Ups. 3.
(2012). Structure-Based Audio Fingerprinting for Music Retrieval. ISMIR. p. 55--60.
Grosche, Peter and M{\"u}ller, Meinard(2012). Toward characteristic audio shingles for efficient cross-version music retrieval. Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on. p. 473--476.
(2011). Tempogram toolbox: Matlab implementations for tempo and pulse analysis of music recordings. Proceedings of the 12th International Conference on Music Information Retrieval (ISMIR), Miami, FL, USA. p. 24--28.
(2011). Analyzing Chroma Feature Types for Automated Chord Recognition. Proc. of 42nd AES Conference.
(2011). A Segment-based Fitness Measure for Capturing Repetitive Structures of Music Recordings. 12th International Conference on Music Information Retrieval. p. 615--620.
(2011). Signal Models for and Fusion of Multimodal Information. Dagstuhl Reports, Schloss Dagstuhl-Leibniz-Zentrum für Informatik. 1. p. 97.
M{\"u}ller, Meinard and Goto, Masataka and Dixon, Simon(2011). Multimodal music processing (dagstuhl seminar 11041). Dagstuhl Reports. 1. (1).
(2010). A Novel Timeline Adjustment Functionality for the Interpretation Switcher. ISMIR late-breaking demo.
(2010). What Makes Beat Tracking Difficult? A Case Study on Chopin Mazurkas. ISMIR. p. 649--654.
(2010). Automated analysis of performance variations in folk song recordings. Proceedings of the international conference on Multimedia information retrieval. p. 247--256.
(2010). Tempobasierte Segmentierung von Audioaufnahmen. Deutsche Jahrestagung für Akustik (DAGA).
Grosche, Peter and M{\"u}ller, Meinard and Kurth, Frank(2010). Cyclic tempogram—A mid-level tempo representation for musicsignals. 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. p. 5522--5525.
(2009). Towards automated processing of folk song recordings. Dagstuhl Seminar Proceedings.
(2009). Combination of Onset-Features with Applications to High-Resolution Music Synchronization. NAG/DAGA 2009 International Conference on Acoustics. p. 357--360.
(2009). Robust segmentation and annotation of folk song recordings. Untitled Event. p. 735--740.
(2009). High resolution audio synchronization using chroma onset features. Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on. p. 1869--1872.
(2009). Computing predominant local periodicity information in music recordings. Applications of Signal Processing to Audio and Acoustics, 2009. WASPAA'09. IEEE Workshop on. p. 33--36.
(2009). 09051 Abstracts Collection--Knowledge representation for intelligent music processing. Dagstuhl Seminar Proceedings.
(2009). A Mid-Level Representation for Capturing Dominant Tempo and Pulse Information in Music Recordings. ISMIR. p. 189--194.
(2018). Content-based Methods for Knowledge Discovery in Music. Springer Handbook of Systematic Musicology. p. 823--840. Springer, Berlin, Heidelberg
(2017). Music Information Retrieval.
(2014). D7. 1: BRIDGET Authoring Tools and Player--Report--Version A.
(2014). Unsupervised Music Structure Annotation by Time Series Structure Features and Segment Similarity. IEEE TRANSACTIONS ON MULTIMEDIA. 16. (5). p. 1229--1240. IEEE
Serra, Joan and M{\"u}ller, Meinard and Grosche, Peter and Arcos, Josep Ll(2012). The importance of detecting boundaries in music structure annotation. Proceedings of the Music Information Retrieval Evaluation eXchange (MIREX).
(2012). Analyzing and visualizing repetitive structures in music recordings.
Grosche, Peter and Schuller, Bj{\"o}rn and M{\"u}ller, Meinard and Rigoll, Gerhard(2012). Automatic transcription of recorded music. Acta Acustica united with Acustica. 98. (2). p. 199--215. S. Hirzel Verlag
Schreiber, Hendrik and Grosche, Peter and M{\"u}ller, Meinard(2011). A Re-ordering Strategy for Accelerating Index-based Audio Fingerprinting.
(2010). Extracting predominant local pulse information from music recordings. IEEE Transactions on Audio, Speech, and Language Processing. 19. (6). p. 1688--1701. IEEE
Automatic Mixing for Immersive Teleconferencing Systems Christian Schörkhuber1, Matthias Frank1, Franz Zotter1, Robert Höldrich1, Peter Grosche2.