… as follows:(1) ∧ c ( Y ) = l o g p ( Y | λ c ) − l o g p ( Y | λ u b m ) (2) c ˆ = arg max c = 1 N ∧
c where Y is a sequence of MFCC features of a test speech sample. Accent/language/…

… speaker identification and speaker verification. The process of identifying an unknown speaker
from a set of known speakers is speaker … The acoustic feature sequence is obtained from …

… The study showed that the speaker trait is primarily a deterministic short-time feature rather
… that aggregated the variable-length input sequence into an utterance level representation. …

… sequence as the objective function to train it. This training procedure (LF-MMI) uses a
sequence … it is possible to use automatic speech recognition technology to search for relevant …

… of the sequence. For any given timestep t c in a … Speaker Identification task. The dataset
was manually prepared in three languages: Arabic, English, and Polish for 24 speakers with a bit …

… In both models, the sequence of the main building blocks is similar. The input feature map
is … The residual part of the ResNet-34 exhibits the same block sequence, with the difference …

… In this paper a systematic survey on Automatic Speech Recognition (ASR) for tonal …
signal and classify it as the last learned pattern in a sequence. The performance as well as …

… and produces a sequence of speaker embeddings on its … a built-in voice activity detection
module based on a single-… compare the results on the speaker verification task of the original …

… -to-end speech recognition model trained with KsponSpeech. … be considered in spontaneous
speech recognition in Korean. … -art speech recognition with sequence-to-sequence models. …

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model training
problematic for most existing languages, including languages that do not even have a …