KALAKA-3: a database for the assessment of spoken language recognition technology on YouTube audios

By Luis Javier Rodriguez-Fuentes, Mikel Peñagarikano, Amparo Varona, Mireia Díez, Germán Bordel. 2015

17 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Evaluation & Benchmarks, Speech & Audio, Signal Processing

How researchers see this paper

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

In Artificial Intelligence

1. Tanel Alumäe
2. Jörgen Valk

In Evaluation & Benchmarks

1. Tanel Alumäe
2. Jörgen Valk

In Speech & Audio

1. Tanel Alumäe
2. Jörgen Valk

In Signal Processing

1. Tanel Alumäe
2. Jörgen Valk

Citations in the corpus

• VOXLINGUA107: A Dataset for Spoken Language Recognition (2020, methodology): “The KALAKA-3 database [3] contains varying amounts of data from YouTube for several European languages.”