On Similarity and Density of Applause Sounds

By Alexander Adami, Armin Taghipour, J. Herre. 2017

7 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Speech and Hearing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. D. Jia
2. Arijit Biswas

In Speech and Hearing

1. D. Jia
2. Arijit Biswas

Citations in the corpus

• Audio Codec Enhancement with Generative Adversarial Networks (2020, methodology): “For applause, we analyzed available sound effects CDs referenced in [7] and found that most of the applause signals are contaminated with crowd noise and are not necessarily difficult for coding.”