Why reduce? Phonological neighborhood density and phonetic reduction in spontaneous speech

By Susanne Gahl, Yao Yao, Keith Johnson. 2012

288 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology, Language and Linguistics

View Paper: https://www.semanticscholar.org/paper/b096d452662ee96c96813df753ac0b60f70e9eaf

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. James Bartolotti
2. Viorica Marian
3. Morgan Sonderegger
4. Anthony Shook
5. Sarah Chabal
6. Hung-yi Lee
7. Xu Tan
8. Tao Qin

In Experimental and Cognitive Psychology

1. Viorica Marian
2. Aneta Pavlenko
3. J. V. Hell
4. Darren Tanner
5. Margarita Kaushanskaya
6. Judith F. Kroll

In Language and Linguistics

1. Viorica Marian

Citations in the corpus

• CLEARPOND: Cross-Linguistic Easy-Access Resource for Phonological and Orthographic Neighborhood Densities (2012, background): “processes differently [16,17], and effects may vary depending on the language of presentation [13,18,19] (but see [14]).”
• Montreal Forced Aligner: Trainable Text-Speech Alignment Using Kaldi (2017, methodology): “The CVC words in Buckeye were those from the list of [25], with the additional criterion of having all three segments realized in some way according to the manual transcription.”