[PDF] Top 20 High Level Approaches to Confidence Estimation in Speech Recognition

... the speech as a sequence of ...of confidence estimation was to disentangle the correlative effects of the language ...a recognition with that of a word-level recognizer with the degree ... See full document

... quality estimation is similar to its MT counterpart where research focused on quality predictions at word level (Ueffing and Ney, 2007; Bach et ...sentence level (Specia et al., 2009; Mehdad et al., ... See full document

... phrase-based confidence measures perform very ...two approaches and the one calculated over a window of target ...a high correct acceptance ... See full document

... HMM-based speech recognizer was selected as the frame-based baseline ...phoneme recognition accuracy, based on speech utterances in the development set, were used for the baseline ... See full document

... one-stage speech recognition, the multi-stage speech recognition can significant- ly reduce computation ...multi-stage speech recognition is repeated for every phoneme in the ... See full document

... In speech recognition, it is desirable to have a confidence score which has a strong correlation with the correctness of ...wrong recognition, and a high score should signal correct ... See full document

... Since ASR is not the focus of our research, for experimental purposes we feed audio instances along with the corresponding text. We study the output of these separate classifiers in terms of probability distributions. ... See full document

... the speech recognition hypotheses. Several approaches for computing confidence measures have been studied in the past ...[10] confidence measures were used to highlight words with low ... See full document

... word- level time boundaries, which prevented us to com- pute more discriminative features like word log- energies, noise log-energies and signal-to-noise ratio (the best indicator of the acoustic quality of an ... See full document

... We estimate N ˆ and ERR separately. There- fore, our system is capable of estimating the WER at different levels of granularity. We visualise the prediction per program. In scenarios such as media-monitoring, where the ... See full document

... This method in [7] computes a set of features from the signal which can be divided into long-term features and frame-based features. The former features are taken from long-term average speech spectrum (LTASS) ... See full document

... An important research regarding this topic was presented by [5]. Their approach consisted of a modified web browser interface controlled through subvocal electromyogram. The signals were measured on the side of the ... See full document

... In the next step i.e. when signal is passed through Mel filter Bank which is made up of triangle shaped overlapping filter the Hertz signal will be converted into Mel scale [8]. The DCT of the output from Mel filter ... See full document

... format that contains audio data in Dolby Digital (AC-3) (six channel) format. Then, the audio channel that con- tains the dialogues was separated from other audio chan- nels for each movie and saved as a separate file at ... See full document

... A speech synthesizer converts written text into spoken language. Speech synthesis is also referred to as Text-To- Speech (TTS) ...the speech can be produced from the phoneme and prosody ... See full document

... of Speech Recognition System for ME Speech recognition system accepts ME audio signal in the form of ...from speech signal in the form of fix size acoustic ...frame level ... See full document

... Spontaneous Speech Effects In Large Vocabulary Speech Recognition Applications Spontaneous Speech Effects In Large Vocabulary Speech Recognition Applications John Butzberger, Hy Murveit, Elizabeth Shr[.] ... See full document

... We worked with a very limited feature set here, drawing on intuitions from previous work on in- teractive translation prediction. One could cer- tainly explore a wide range of more complex fea- tures, such as the number ... See full document

... Feature values were automatically computed from system logs, based on five types of knowledge sources: acoustic, dialogue efficiency, dialogue quality, experimental parameters, and lexic[r] ... See full document

... the speech resulting in a set of feature ...is recognition which consists of two phases- training and ...of speech so that we may get a set of representatives to classify them into different ... See full document