The MITLL NIST LRE 2007 language recognition system

By Pedro A. Torres-Carrasquillo, Elliot Singer, William M. Campbell, Terry P. Gleason, Alan McCree, D. A. Reynolds, Fred Richardson, Wade Shen, Douglas E. Sturim. 2008

41 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Speech & Audio

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. Haizhou Li
2. Bin Ma
3. Kong Aik LEE
4. Berrak Sisman
5. Sakriani Watiasri Sakti
6. Xu Tan

In Computer Vision and Pattern Recognition

1. Kong Aik LEE
2. Haizhou Li

In Speech & Audio

1. Haizhou Li
2. Bin Ma
3. Kong Aik LEE

Citations in the corpus

• VOXLINGUA107: A Dataset for Spoken Language Recognition (2020, neutral): “System 3 sec 10 sec 30 sec Average Trained on in-domain data (telephone speech) GMM-MMI [24] 17.28 5.90 2.10 8.42 Fusion of models [24] 13.32 3.55 0.97 5.95 Phonotactic [25] 18.59 6.28 1.34 8.73 Fusion of models [25] 15.29 4.54 1.30 7.04 Kaldi i-vector 6 26.04 11.”
• Spoken Language Recognition: From Fundamentals to Practice (2013, background): “As GMM tokenization does not attempt to relate a Gaussian label with an acoustic– phonetic event, it does not require transcribed speech data for model training.”