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Single Word Error Rate

lies in the fact that the recognized word sequence can have a different length from the reference word sequence (supposedly the correct one). The WER is derived from the Levenshtein distance, working at the word level instead of the phoneme

Word Error Rate Example

level. The WER is a valuable tool for comparing different systems as well as for word error rate python evaluating improvements within one system. This kind of measurement, however, provides no details on the nature of translation errors and further work is

Word Error Rate Calculation Tool

therefore required to identify the main source(s) of error and to focus any research effort. This problem is solved by first aligning the recognized word sequence with the reference (spoken) word sequence using dynamic string alignment. Examination of word error rate in mobile communication this issue is seen through a theory called the power law that states the correlation between perplexity and word error rate.[1] Word error rate can then be computed as: W E R = S + D + I N = S + D + I S + D + C {\displaystyle {\mathit {WER}}={\frac {S+D+I}{N}}={\frac {S+D+I}{S+D+C}}} where S is the number of substitutions, D is the number of deletions, I is the number of insertions, C is word error rate algorithm the number of the corrects, N is the number of words in the reference (N=S+D+C) The intuition behind 'deletion' and 'insertion' is how to get from the reference to the hypothesis. So if we have the reference "This is wikipedia" and hypothesis "This _ wikipedia", we call it a deletion. When reporting the performance of a speech recognition system, sometimes word accuracy (WAcc) is used instead: W A c c = 1 − W E R = N − S − D − I N = H − I N {\displaystyle {\mathit {WAcc}}=1-{\mathit {WER}}={\frac {N-S-D-I}{N}}={\frac {H-I}{N}}} where H is N-(S+D), the number of correctly recognized words. IF I=0 then WAcc will be equivalent to Recall (information retrieval) a ratio of correctly recognized words 'H' to Total number of words in reference 'N'. Note that since N is the number of words in the reference, the word error rate can be larger than 1.0, and thus, the word accuracy can be smaller than 0.0. This problem can be overcome by using the hit rate with respect to the total number of test-reference match pairs found by the matching process used in scoring, (H+S+D+I), rather than with respect to the number of reference words, (H+S+D). This gives the match-accuracy rate as MAcc = H/(H+S+D+I) and match error rate, MER = 1-MAcc = (S+D+I)/(H+S+D+I).[2] WAcc and WER as defined abo

an hypothesis and is defined like this: $$\mathit{WER} = \frac{S+D+I}{N}$$ where S is the number of substitutions, D is the number of deletions, I is the number of insertions and

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N is the number of words in the reference Examples REF: What a sentence error rate bright day HYP: What a day In this case, a deletion happened. "Bright" was deleted by the ASR. REF:

Word Error Rate Tool

What a day HYP: What a bright day In this case, an insertion happened. "Bright" was inserted by the ASR. REF: What a bright day HYP: What a light day In this https://en.wikipedia.org/wiki/Word_error_rate case, an substitution happened. "Bright" was substituted by "light" by the ASR. Range of values As only addition and division with non-negative numbers happen, WER cannot get negativ. It is 0 exactly when the hypothesis is the same as the reference. WER can get arbitrary large, because the ASR can insert an arbitrary amount of words. Calculation Interestingly, the WER is just the https://martin-thoma.com/word-error-rate-calculation/ Levenshtein distance for words. I've understood it after I saw this on the German Wikipedia: \begin{align} m &= |r|\\ n &= |h|\\ \end{align} \begin{align} D_{0, 0} &= 0\\ D_{i, 0} &= i, 1 \leq i \leq m\\ D_{0, j} &= j, 1 \leq j \leq n \end{align} $$ \text{For } 1 \leq i\leq m, 1\leq j \leq n\\ D_{i, j} = \min \begin{cases} D_{i - 1, j - 1}&+ 0 \ {\rm if}\ u_i = v_j\\ D_{i - 1, j - 1}&+ 1 \ {\rm(Replacement)} \\ D_{i, j - 1}&+ 1 \ {\rm(Insertion)} \\ D_{i - 1, j}&+ 1 \ {\rm(Deletion)} \end{cases} $$ But I have written a piece of pseudocode to make it even easier to code this algorithm: WER calculation Python #!/usr/bin/env python def wer(r, h): """ Calculation of WER with Levenshtein distance. Works only for iterables up to 254 elements (uint8). O(nm) time ans space complexity. Parameters ---------- r : list h : list Returns ------- int Examples -------- >>> wer("who is there".split(), "is there".split()) 1 >>> wer("who is there".split(), "".split()) 3 >>> wer("".split(), "who is there".split()) 3 """ # initialisation import numpy d = numpy.zeros((len(r)+1)*(len(h)+1)

in Speech recognition? Except PER metric, what are the existing performance metrics to compare two different recognizers in speech recognition? Topics Speech https://www.researchgate.net/post/What_are_the_performance_measures_in_Speech_recognition Recognition Software × 25 Questions 88 Followers Follow Computational Linguistics × 147 http://www.verbyx.com/ASR_Accuracy.html Questions 11,378 Followers Follow Speech Recognition × 133 Questions 2,131 Followers Follow Nov 4, 2014 Share Facebook Twitter LinkedIn Google+ 0 / 0 All Answers (5) Raivis Skadiņš · Tilde Company I think that Word Error Rate (WER) is the metric everybody is using. Nov 6, 2014 error rate Yun-Nung (Vivian) Chen · Microsoft In addition to Word Error Rate, some people use Word Accuracy as well. Nov 6, 2014 Mirco Ravanelli · Fondazione Bruno Kessler As pointed out, the most common measure is the so called word error rate (WER%). Such a performance is computed by comparing a reference transcription with the transcription output by the word error rate speech recognizer. From this comparison it is possible to compute the number of errors, which typically belong to 3 categories: -Insertions I (when in the output of the ASR it is present a word not present in the reference)-Deletions D(a word is missed in the ASR output)-Substitutions S (a word is confused with another one) WER= (S+D+I)/N Where N is the number of words in the reference transcription. The main issue in computing this score is the needed alignment between the 2 word sequences. This can be obtained through dynamic programming, using the so called Levenstein distance. Fortunately, you can find on-line several tool to compute it… Mirco https://sites.google.com/site/mircoravanelli/ Nov 6, 2014 Homayoon Beigi · Recognition Technologies, Inc. Although Mirco is correct and indeed many papers use this measure, I just want to add one point of caution.  The formula which is given is normalized against the prompt, so it is possible to get error rates that are greater than 100%, using this formula -- i.e., when I > D, namely when the length

/ ASR Accuracy ASR Accuracy The Numbers!   One measure of the performance of an ASR is accuracy - or how well it recognizes utterances. Recognition accuracy is dependent on many factors, one being the design of the language model. There is little point in building a great ASR if in operation, your language model does not support technical words and phrases that might be spoken during the dialog. Often ASR vendors report an accuracy of over 99%, but what does that term mean? And is it of any value to your application? Accuracy is a quantitative measurement and is often quoted in the form of an error rate. Error rates can be calculated in several ways. Key ASR Error Rates Word Error Rate This is the most commonly quoted measurement of accuracy. Word error rate (WER) represents the number of words recognized incorrectly from the total number of words spoken. It can be a useful measurement when validating language models. A significant problem in using WER as a measure is that it often does not give an indication of usability. If during a dialog with a user, the ASR returned "NOPE" when the user said "NO", this would be considered a recognition error. In practice however, both words have the same semantic meaning. WER can often be reduced by analysis of your grammar. For instance, adding "nope" as a valid word.. Digit Error Rate Digit error rate (DER) is a similar to WER, it is calculated in an identical manner. In some applications, it can be difficult to achieve high digit accuracies. If digits are important to your application, make sure that you specifically ask about digit performance. Sentence Error Rate When measuring sentence error rate (SER), the returned sentence (hypothesis) is compared against the spoken audio (reference). If the hypothesis does not match the reference exactly then the SER is 100%. For example, the user says "I would like to speak to the accounting department please" and the ASR returns. "I would like to speak with

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Seek Error Rate Raw Read Error Rate p a large number for Seek error rate attribute note that I edited the output for readability Vendor Specific SMART Attributes with Thresholds ID ATTRIBUTE NAME FLAG VAL WOR THR TYPE UPDATED WHEN FAILED RAW VALUE Raw Read Error Rate x f Pre-fail Always - Spin Up Time what is seek error rate x Pre-fail Always - Start Stop Count p Seek Error Rate Fix p x Old age Always - Reallocated Sector Ct x Pre-fail Always - p Seek Error Rate Western Digital p Seek Error Rate x f Pre-fail Always -

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Seek Error Rate Western Digital p p p Value Threshold Worst Warranty Raw Read Error Rate p Hardware ecc recovered p p What Is Raw Read Error Rate p Spin Up Time seagate high seek error rate Start Stop Count a href http www tomshardware com answers id- high-seek-error-rate-smart html http www tomshardware com answers id- high-seek-error-rate-smart html a Re-allocated Sector The rest of the thresholds are so if the Values and Worst values are needed please let me know The SMART result a href https community wd com t interpreting-smart-results https community wd com t interpreting-smart-results a is PASS

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Seek Error Rate Seagate tb p a large number for Seek error rate attribute note that I edited the output for readability Vendor Specific SMART Attributes with Thresholds ID ATTRIBUTE NAME FLAG VAL WOR THR TYPE UPDATED WHEN FAILED RAW VALUE Raw Read Error Rate x f Pre-fail Always what is seek error rate - Spin Up Time x seek error rate fix Pre-fail Always - Start Stop Count x Old age Always - p Seek Error Rate Western Digital p Reallocated Sector Ct x Pre-fail Always - Seek Error Rate x f Pre-fail Always - Power On Hours x

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Smart High Seek Error Rate p tech Search Tags Builds Cases Cooling CPUs Graphics Laptops Memory Monitors Motherboards more Peripherals PSUs Storage VR ForumStorage Seek error rate drevinJan AM I have some questions about the seek error rate SMART attribute I have a Seagate Gb about years what is seek error rate old that has a high seek error rate I know that the raw data field has a different seek error rate fix structure for different vendors and is thus not very meaningful However what concerns me is that the current and worst fields have also decreased a seek

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Smart Read Error Rate Seagate p a large number for Seek error rate attribute note that I edited the output for readability Vendor Specific SMART Attributes with Thresholds ID ATTRIBUTE NAME FLAG VAL WOR THR TYPE UPDATED WHEN FAILED RAW VALUE Raw Read Error Rate x f Pre-fail Always - Spin Up Time p What Is Seek Error Rate p x Pre-fail Always - Start Stop Count seek error rate seagate x Old age Always - Reallocated Sector Ct x Pre-fail Always - seek error rate fix Seek Error Rate x f Pre-fail Always - Power On Hours x Old

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Smart Raw Read Error Rate Seagate p a large number for Seek error rate attribute note that I edited the output for readability Vendor Specific SMART Attributes with Thresholds ID ATTRIBUTE NAME FLAG VAL WOR THR TYPE UPDATED WHEN FAILED RAW VALUE Raw Read Error Rate x f Pre-fail Always - Spin Up Time what is seek error rate x Pre-fail Always - seek error rate seagate Start Stop Count x Old age Always - Reallocated Sector Ct x Pre-fail Always - seek error rate fix Seek Error Rate x f Pre-fail Always - Power On Hours x Old age

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Smart Seek Error Rate p tech Search Tags Builds Cases Cooling CPUs Graphics Laptops Memory Monitors Motherboards more Peripherals PSUs Storage VR ForumStorage high seek error rate on smart DipayanJul AM I have hdd st is seek error rate seagate gb os is installed on it and nd is tb My tb hdd is fairy new been p What Is Seek Error Rate p used for hours only but sometime when downloading files on it i have seem to notice that the other files present seek error rate fix on it are playing slowly sometimes the folders wont even open

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Smart Multi Zone Error Rate p Technology - unRAID Server Community Community Storage Devices and Controllers Multi Zone Error Rate again laquo previous next raquo Send this topic hd sj read error rate or write error rate Print Pages Go Down Author Topic Multi Zone Error Rate again Read p Raw read error rate Smart p times PeterB Community Developer Hero Member Posts Multi Zone Error Rate again on March AM offline uncorrectable One of my drives a WD EADS which was redeployed from my media player in to unRAID and is now months old is showing a 'Multi Zone

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Smart Seagate Read Error Rate p a large number for Seek error rate attribute note that I edited the output for readability Vendor Specific SMART Attributes with Thresholds ID ATTRIBUTE NAME FLAG VAL WOR THR TYPE UPDATED WHEN FAILED RAW VALUE Raw Read Error Rate x f Pre-fail Always - p What Is Seek Error Rate p Spin Up Time x Pre-fail Always seek error rate seagate - Start Stop Count x Old age Always - Reallocated Sector Ct x p Seek Error Rate Fix p Pre-fail Always - Seek Error Rate x f Pre-fail Always - Power On Hours