Abstract: Methods, apparatuses and systems for calibrating gas detectors are disclosed. An example calibration apparatus may have a gas supply element configured to provide a background gaseous substance within at least a portion of the calibration apparatus, a nebulizing element configured to generate the testing gaseous substance by transforming a testing solution in conjunction with the background gaseous substance, a pressure control element configured to regulate airflow in order to maintain a constant air pressure within the at least a portion of the calibration apparatus, and a controller component in electronic communication with the gas supply element, the nebulizing element and the pressure control element.

Abstract: A screw compressor slide valve with gas pulsation attenuation function includes valve walls and internal through holes. A screw compressor includes the screw compressor slide valve. A part of exhausted gas of the screw compressor is directly discharged from an exhaust port to an exhaust chamber to form a main exhaust flow channel; another part of the exhausted gas is discharged from the exhaust port into the exhaust chamber after being delayed by the internal through holes, which forms a branched exhaust flow channel. Since the branched exhaust flow channel is longer than the main exhaust flow channel, when the gas pulsation in the branched exhaust flow channel lags behind that in the main exhaust flow channel by 180-degree in phase, two gas pulsations in the two flow channels are offset due to opposite gas pulsation phases, which attenuates the gas pulsation, thereby suppressing induced vibration and noise.

Abstract: Provided are a 4-sulfur pentafluoride phenol compound and a preparation method therefor, and a preparation method for a sulfur pentafluoride substituted benzopyran compound. According to the present invention, sulfur pentafluoride salicylaldehyde with multiple substituent groups is synthesized through a plurality of steps by using sulfur pentafluoride phenol as a raw material, and then the sulfur pentafluoride substituted benzopyran compound is synthesized on this basis. The method is simple and convenient, and low in cost; overcomes the defects that, at present, the number of types of sulfur pentafluoride phenols is small, and the synthesis of various sulfur pentafluoride substituted benzopyran compounds cannot be met; and has wide industrial application prospects.

Abstract: Provided are a 4-sulfur pentafluoride phenol compound and a preparation method therefor, and a preparation method for a sulfur pentafluoride substituted benzopyran compound. According to the present invention, sulfur pentafluoride salicylaldehyde with multiple substituent groups is synthesized through a plurality of steps by using sulfur pentafluoride phenol as a raw material, and then the sulfur pentafluoride substituted benzopyran compound is synthesized on this basis. The method is simple and convenient, and low in cost; overcomes the defects that, at present, the number of types of sulfur pentafluoride phenols is small, and the synthesis of various sulfur pentafluoride substituted benzopyran compounds cannot be met; and has wide industrial application prospects.

Abstract: A method for speech recognition is implemented in the specific form of computer processes that function in a computer processor. That is, one or more computer processes: process a speech input to produce a sequence of representative speech vectors and perform multiple recognition passes to determine a recognition output corresponding to the speech input. At least one generic recognition pass is based on a generic speech recognition arrangement using generic modeling of a broad general class of input speech. And at least one adapted recognition pass is based on a speech adapted arrangement using pre-adapted modeling of a specific sub-class of the general class of input speech.

Abstract: Adjusting model parameters is described for a speech recognition system that combines recognition outputs from multiple speech recognition processes. Discriminative adjustments are made to model parameters of at least one acoustic model based on a joint discriminative criterion over multiple complementary acoustic models to lower recognition word error rate in the system.

Abstract: A method for speech recognition is implemented in the specific form of computer processes that function in a computer processor. That is, one or more computer processes: process a speech input to produce a sequence of representative speech vectors and perform multiple recognition passes to determine a recognition output corresponding to the speech input. At least one generic recognition pass is based on a generic speech recognition arrangement using generic modeling of a broad general class of input speech. And at least one adapted recognition pass is based on a speech adapted arrangement using pre-adapted modeling of a specific sub-class of the general class of input speech.

Abstract: Methods are given for improving discriminative training of hidden Markov models for continuous speech recognition. For a mixture component of a hidden Markov model state, a gradient adjustment is calculated of the standard deviation of the mixture component. If the calculated gradient adjustment is greater than a first threshold amount, an adjustment is performed of the standard deviation of the mixture component using the first threshold. If the calculated gradient adjustment is less than a second threshold amount, an adjustment is performed of the standard deviation of the mixture component using the second threshold. Otherwise, an adjustment is performed of the standard deviation of the mixture component using the calculated gradient adjustment.

Abstract: Adjusting model parameters is described for a speech recognition system that combines recognition outputs from multiple speech recognition processes. Discriminative adjustments are made to model parameters of at least one acoustic model based on a joint discriminative criterion over multiple complementary acoustic models to lower recognition word error rate in the system.

Abstract: Methods are given for improving discriminative training of hidden Markov models for continuous speech recognition. For a mixture component of a hidden Markov model state, a gradient adjustment is calculated of the standard deviation of the mixture component. If the calculated gradient adjustment is greater than a first threshold amount, an adjustment is performed of the standard deviation of the mixture component using the first threshold. If the calculated gradient adjustment is less than a second threshold amount, an adjustment is performed of the standard deviation of the mixture component using the second threshold. Otherwise, an adjustment is performed of the standard deviation of the mixture component using the calculated gradient adjustment.

Abstract: Speech recognition includes use of a user profile for large vocabulary continuous speech recognition which is created without using an enrollment procedure. The user profile includes speech recognition information associated with a specific user. Large vocabulary continuous speech recognition is performed on an unknown speech input from the user utilizing the information from the user profile.

Abstract: The invention is a system and method for automatic acoustic speaker adaptation in an automatic speech recognition assisted transcription system. Partial transcripts of audio files are generated by a transcriptionist. A topic language model is generated from the partial transcripts. The topic language model is interpolated with a general language model. Automatic speech recognition is performed on the audio files by a speech recognition engine using a speaker independent acoustic model and the interpolated language model to generate semi-literal transcripts of the audio files. The semi-literal transcripts are then used with the corresponding audio files to generate a speaker dependent acoustic model in an acoustic adaptation engine.

Abstract: Methods are given for improving discriminative training of hidden Markov models for continuous speech recognition. In one approach, discriminatively trained mixture models are interpolated with maximum likelihood trained mixture models. In another approach, segmentation and recognition results from one set of models are reused to discriminatively train a second set of models. For example, segmentation and recognition results from detailed match models are mapped and used to discriminatively train fast match models. In addition, gradients for the standard deviation of mixture components are clipped based on the statistics of the gradients. Pronunciation of words may also be used to determine the “incorrect” recognition hypothesis.

Abstract: The invention is a system and method for automatic acoustic speaker adaptation in an automatic speech recognition assisted transcription system. Partial transcripts of audio files are generated by a transcriptionist. A topic language model is generated from the partial transcripts. The topic language model is interpolated with a general language model. Automatic speech recognition is performed on the audio files by a speech recognition engine using a speaker independent acoustic model and the interpolated language model to generate semi-literal transcripts of the audio files. The semi-literal transcripts are then used with the corresponding audio files to generate a speaker dependent acoustic model in an acoustic adaptation engine.