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han zed depending on region an 8 error rate is considered good for this vocabulary 155 speaker dependence vs independence a speaker dependent system is intended for use by a single speaker a speaker independent system is intended for use by any speaker more difficult 156 isolated discontinuous or continuous speech with isolated speech single words are used which is easier to recognize with discontinuous speech full sentences separated by silence are used the silence is easier to recognize similar to isolated speech with continuous speech naturally spoken sentences are used which are harder to recognize task and language constraints can inform the recognition the requesting application may dismiss the hypothesis the apple is red constraints may be semantic rejecting the apple is angry syntactic rejecting red is apple the constraints are often represented by grammar read vs spontaneous speech when a person reads it s usually in a context that has been previously prepared when a person speaks spontaneously recognition must deal with disfluencies such as uh and um false starts incomplete sentences stuttering coughing and laughter and limited vocabulary adverse conditions environmental noise e g in a car or factory acoustic distortions e g echoes room acoustics speech recognition is a multi level pattern recognition task acoustic signals are structured into a hierarchy of units e g phonemes words phrases and sentences each level provides additional constraints e g known word pronunciations or legal word sequences which can compensate for errors or uncertainties at a lower level this hierarchy of constraints improves accuracy by combining decisions probabilistically at all lower levels and making ultimate decisions only at the highest level speech recognition is broken into several phases computationally it is a problem in which a sound pattern has to be recognized or classified into a category that represents a meaning to a human every acoustic signal can be broken into smaller sub signals as the more complex sound signal is divided different levels are created where at the top level are complex sounds made of simpler sounds on the lower level etc at the lowest level simple and more probabilistic rules apply these sounds are put together into more complex sounds on upper level a new set of more deterministic rules predicts what the complex sound represents the upper level of a deterministic rule should figure out the meaning of complex expressions in order to expand our knowledge about speech recognition we need to take into consideration neural networks neural network approaches use the following steps digitize the speech for telephone speech 8000 samples per second are captured 157 compute features of spectral domain of the speech with fourier transform computed every 10ms with one 10ms section called a frame sound is produced by air or some other medium vibration sound creates a wave that has two measures amplitude strength and frequency vibrations per second 158 accuracy can be computed with the help of wer which is calculated by aligning the recognized word and referenced word using dynamic string alignment the problem may occur while computing the wer due to the difference between the sequence lengths of the recognized word and referenced word the formula to compute the word error rate wer is w e r s d i n displaystyle wer s d i over n where s is the number of substitutions d is the number of deletions i is the number of insertions and n is the number of word references 159 while computing the word recognition rate wrr is used the formula is w r r 1 w e r n s d i n h i n displaystyle wrr 1 wer n s d i over n h i over n where h is the number of correctly recognized words h n s d displaystyle h n s d security edit speech recognition can become a means of attack theft or accidental operation for example activation words like alexa spoken in an audio or video broadcast can cause devices in homes and offices to start listening for input inappropriately or possibly take an unwanted action 160 voice controlled devices may be accessible to unauthorized users attackers may be able to gain access to personal information like calendars address book contents private messages and documents they may also be able to impersonate the user to send messages or make online purchases two attacks have been demonstrated that use artificial sounds one transmits ultrasound and attempts to send commands without people noticing 161 the other adds small inaudible distortions to other speech or music that are specially crafted to confuse the specific speech recognition system into recognizing music as speech or to make what sounds like one command to a human sound like a different command to the system 162 further information edit conferences edit regular conferences include speechtek and speechtek europe icassp interspeech eurospeech and the ieee asru conferences in the field of natural language processing such as acl naacl emnlp and hlt include papers on speech processing journal edit the main journal is ieee acm transactions on audio speech and language processing books edit fundamentals of speech recognition by lawrence rabiner 1993 statistical methods for speech recognition by frederick jelinek spoken language processing by xuedong huang et al 2001 computer speech by manfred r schroeder 2004 speech processing a dynamic and optimization oriented approach by li deng and doug o shaughnessey 2003 speech and language processing by jurafsky and martin 2008 fundamentals of speaker recognition in depth source for up to date details on the theory and practice 163 the voice in the machine building computers that understand speech by roberto pieraccini 2012 introduction automatic speech recognition a deep learning approach by microsoft researchers d yu and l deng 2014 mathematically oriented treatment of deep learning methods are 88 deep learning methods and applications by l deng and d yu 2014 methodology focused overview of dnn based speech recognition 84 projects edit the largest speech recognition related project ongoing as of 2007 was the gale project which involves both speech recognition and translation components software edit sphinx toolkit is one starting point for experimenting with speech recognition htk book and accompanying toolkit kaldi toolkit can be used 164 common voice 165 166 uses tensorflow 167 coqui stt 168 derived from common voice using the same open source license 169 170 gboard supports speech recognition on all android applications 171 speech recognition is available in microsoft windows operating systems 172 commercial cloud based speech recognition apis are broadly available see also edit ai effect alpac application language tags for speech recognition articulatory speech recognition audio mining audio visual speech recognition automatic language translator automotive head unit braina cache language model dragon naturallyspeaking fluency voice technology 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a hybrid approach the kluwer internati...