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Michael Neumann

University of Stuttgart

4 papers hereh-index 10623 citations13 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.SD1
affiliations
  • University of Stuttgart
  • Modality.AI
Homepage
same name
  • Michael Neumann — 4 papers
  • Michael Neumann — 1 paper, h 4
  • Michael Neumann — 1 paper
  • Michael Neumann — 1 paper
  • Michael Neumann — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172021
most citedAttentive Convolutional Neural Network based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech

2 citations · 3 across the 2 of their papers we have counts for

collaborators
Showing cs.CLShow all

3 papers · 1 filter

cs.CL2020★ 1 cited

ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents

Chia-Yu Li, Daniel Ortega, Dirk Väth +9

We present ADVISER - an open-source, multi-domain dialog system toolkit that enables the development of multi-modal (incorporating speech, text and vision), socially-engaged (e.g.…

cs.CL2018

Cross-lingual and Multilingual Speech Emotion Recognition on English and French

Michael Neumann, Ngoc Thang Vu

Research on multilingual speech emotion recognition faces the problem that most available speech corpora differ from each other in important ways, such as annotation methods or int…

cs.CL2017★ 2 cited

Attentive Convolutional Neural Network based Speech Emotion Recognition: A Study on the Impact of Input Features, Signal Length, and Acted Speech

Michael Neumann, Ngoc Thang Vu

Speech emotion recognition is an important and challenging task in the realm of human-computer interaction. Prior work proposed a variety of models and feature sets for training a…

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