feat: prosody detetction

Presently/presently/users/myprosody/dataset/datanewchi22.csv

+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0

Presently/presently/users/myprosody/dataset/datanewchi23.csv

+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0

Presently/presently/users/myprosody/dataset/datanewchi33.csv

+0,0,0,0,0,0,0,0,0,0,0,0,0,0

Presently/presently/users/myprosody/dataset/datanewchi34.csv

+0,0,0,0,0,0,0,0,0,0,0,0,0,0

Presently/presently/users/myprosody/dataset/datanewchi44.csv

+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0

Presently/presently/users/myprosody/dataset/datanewchi45.csv

+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0

Presently/presently/users/myprosody/dataset/stats.csv

+,average_syll_pause_duration,No._long_pause,speaking_time,ave_No._of_words_in_minutes,articulation_rate,No._words_in_minutes,formants_index,f0_index,f0_quantile_25_index,f0_quantile_50_index,f0_quantile_75_index,f0_std,f0_max,f0_min,No._detected_vowel,perc%._correct_vowel,(f2/f1)_mean,(f2/f1)_std,no._of_words,no._of_pauses,intonation_index,(voiced_syll_count)/(no_of_pause),TOEFL_Scale_Score,Score_Shannon_index,speaking_rate
+count,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0,697.0
+mean,0.8711691505007172,11.884827192525108,61.87325681492109,2.511292756892396,4.356201165370158,105.7234069427116,368.3031599170732,0.9613590789426112,0.9160735395667144,174.86871823299856,0.9603444352639884,46.759814277934005,385.23783471377334,79.08099626984219,84.14060258249641,0.6085482836183644,2.4881832346585364,0.7203101768134863,132.7302725968436,25.53945480631277,7.127690100430416,10.302043154121952,21.968436154949785,2.8686284074605455,3.082425903516499
+std,0.46166177671746383,10.64664213863159,38.27363756344159,0.23284718254288647,0.5018093886478655,21.084760878463424,21.408253503187975,0.11856904287612252,0.15778835368459473,37.224660757224875,0.11898883930794583,14.43561315626036,41.0241155972532,10.493765220484537,48.92913919414536,0.17051676788392314,0.2858284340699538,0.18294312359365827,87.77543914621356,14.871922795434735,1.6372265855189436,9.740952677485364,4.668509323515208,0.6119229333631522,0.6783222980271066
+min,0.32,2.261335451,7.54,1.5615067480000002,3.0,28.00108004,327.06,0.7150403790000001,0.522027013,94.13391354,0.6422109810000001,14.39604874,192.0464154,60.61750438,3.0,0.06122449,1.570231608,0.299595563,15.0,1.0,4.0,1.625,9.0,1.0759999999999998,1.0
+25%,0.663462868,5.881282799,29.07,2.367729993,4.0,93.90385508,352.3382912,0.888699048,0.812169482,151.3014793,0.8920442759999999,35.68453756,371.8891276,72.76623526,41.0,0.47826087,2.278626254,0.601991294,59.0,13.0,6.0,6.551724137999999,20.0,2.52,3.0
+50%,0.7664013609999999,8.38372206,54.24,2.523156338,4.0,108.12892520000001,373.8021607,0.957603522,0.9148756840000001,180.32414269999998,0.948689995,48.18847497,396.0576138,79.05566587,77.0,0.6,2.512143195,0.6963008620000001,113.0,23.0,7.0,8.45,22.0,2.895,3.0
+75%,0.9132467879999999,13.08693878,85.22,2.651778138,5.0,119.9512105,386.7869727,1.0249682979999999,1.036024366,199.34072369999998,1.026649572,58.23745756,416.41539889999996,80.61435463,117.0,0.740740741,2.6869739669999997,0.803898055,181.0,35.0,8.0,11.36842105,26.0,3.32,3.378208354
+max,4.689212121000001,113.15333329999999,225.31,3.3529533639999998,6.0,190.560794,399.6609917,1.427151945,1.442502751,313.60393860000005,1.473006332,84.0325436,424.380037,179.83311369999998,304.0,0.970588235,3.6152396330000003,2.107762509,489.0,93.0,10.0,125.5,29.0,3.96,6.0

Presently/presently/users/prosodydetectionaudio.py

+import myprosody as mysp
+import pickle
+
+p="suun3" 
+c="F:\\CDAP-PRESENTLY\\21_22-j-02\\Presently\\presently\\users\\myprosody" 
+
+
+mysp.myspgend(p,c)
+mysp.mysppron(p,c)
+mysp.myprosody(p,c)
+mysp.mysplev(p,c)

Presently/presently/users/setup.py

+from setuptools import setup
+
+long_description="""*** Version-10 release: two new functions were added ***
+
+The two new functions deploy different Machine Learning algorithms to estimate the speakers' spoken 
+language proficiency levels (only the prosody aspect not semantically).  
+ 
+Prosody is the study of the tune and rhythm of speech and how these features contribute to meaning. 
+Prosody is the study of those aspects of speech that typically apply to a level above that of the individual 
+phoneme and very often to sequences of words (in prosodic phrases). Features above the level of the phoneme 
+(or "segment") are referred to as suprasegmentals. 
+A phonetic study of prosody is a study of the suprasegmental features of speech. At the phonetic level, 
+prosody is characterised by:
+
+1.	vocal pitch (fundamental frequency)
+2.	acoustic intensity
+3.	rhythm (phoneme and syllable duration)
+
+MyProsody is a Python library for measuring these acoustic features of speech (simultaneous speech, high entropy) 
+compared to ones of native speech. The acoustic features of native speech patterns have been observed and 
+established by employing Machine Learning algorithms. An acoustic model (algorithm) breaks recorded utterances 
+(48 kHz & 32 bit sampling rate and bit depth respectively) and detects syllable boundaries, fundamental frequency
+contours, and formants. Its built-in functions recognize/measures:
+
+	Average_syll_pause_duration
+	No._long_pause
+	Speaking-time
+	No._of_words_in_minutes
+	Articulation_rate 
+	No._words_in_minutes
+	formants_index
+	f0_index ((f0 is for fundamental frequency)
+	f0_quantile_25_index
+	f0_quantile_50_index
+	f0_quantile_75_index
+	f0_std
+	f0_max
+	f0_min
+	No._detected_vowel
+	perc%._correct_vowel
+	(f2/f1)_mean (1st and 2nd formant frequencies)
+	(f2/f1)_std
+	no._of_words
+	no._of_pauses
+	intonation_index
+	(voiced_syll_count)/(no_of_pause)
+	TOEFL_Scale_Score
+	Score_Shannon_index
+	speaking_rate
+	gender recognition 
+	speech mood (semantic analysis)
+	pronunciation posterior score 
+	articulation-rate 
+	speech rate
+	filler words 
+	f0 statistics
+	-------------
+	NEW
+	--------------
+	level (CEFR level)
+	prosody-aspects (comparison, native level)
+ 
+The library was developed based upon the idea introduced by Klaus Zechner et al 
+*Automatic scoring of non-native spontaneous speech in tests of spoken English* Speech Communicaion vol 
+51-2009, Nivja DeJong and Ton Wempe [1], Paul Boersma and David Weenink [2], Carlo Gussenhoven [3], 
+S.M Witt and S.J. Young [4] and Yannick Jadoul [5].
+ 
+Peaks in intensity (dB) that are preceded and followed by dips in intensity are considered as potential 
+syllable cores. 
+
+MyProsody is unique in its aim to provide a complete quantitative and analytical way to study acoustic 
+features of a speech. Moreover, those features could be analysed further by employing Python's 
+functionality to provide more fascinating insights into speech patterns. 
+
+This library is for Linguists, scientists, developers, speech and language therapy clinics and researchers.   
+Please note that MyProsody Analysis is currently in initial state though in active development. While the 
+amount of functionality that is currently present is not huge, more will be added over the next few months.
+
+											Installation
+											=============
+Myprosody can be installed like any other Python library, using (a recent version of) the Python package 
+manager pip, on Linux, macOS, and Windows:
+
+										pip install myprosody
+				
+or, to update your installed version to the latest release:
+										
+										pip install -u myprosody
+				
+NOTE:
+============= 
+After installing Myprosody, download the folder called:  
+												
+												myprosody 
+
+from  https://github.com/Shahabks/myprosody
+
+and save on your computer. The folder includes the audio files folder where you will save your audio files 
+for analysis.
+
+Audio files must be in *.wav format, recorded at 48 kHz sample frame and 24-32 bits of resolution.
+
+To check how the myprosody functions behave, please check 
+											
+												EXAMPLES.pdf 
+on  https://github.com/Shahabks/myprosody 
+
+Myprosody was developed by MYOLUTIONS Lab in Japan. It is part of New Generation of Voice Recognition and Acoustic & Language modelling
+Project in MYSOLUTIONS Lab. That is planned to enrich the functionality of Myprosody by adding more advanced 
+functions."""
+	
+	
+setup(name='myprosody',
+      version='10',
+      description='NEW VERSION: the prosodic features of speech (simultaneous speech) compared to the features of native speech +++ spoken language proficiency level estimator',
+	  long_description=long_description,
+	  url='https://github.com/Shahabks/myprosody',
+      author='Shahab Sabahi',
+      author_email='sabahi.s@mysol-gc.jp',
+      license='MIT',
+      classifiers=[
+		'Intended Audience :: Developers',
+		'Intended Audience :: Science/Research',
+		'Programming Language :: Python',
+		'Programming Language :: Python :: 3.7',
+		],
+	  keywords='praat speech signal processing phonetics',
+	  install_requires=[
+		'numpy>=1.15.2',
+		'praat-parselmouth>=0.3.2',
+		'pandas>=0.23.4',
+		'scipy>=1.1.0',
+		'pickleshare>=0.7.5',
+		'scikit-learn>=0.20.2',
+		],
+	  packages=['myprosody'],
+      zip_safe=False)
+	  

Presently/presently/users/stats.csv

+,average_syll_pause_duration,No._long_pause,speaking_time,ave_No._of_words_in_minutes,articulation_rate,No._words_in_minutes,formants_index,f0_index,f0_quantile_25_index,f0_quantile_50_index,f0_quantile_75_index,f0_std,f0_max,f0_min,No._detected_vowel,perc%._correct_vowel,(f2/f1)_mean,(f2/f1)_std,no._of_words,no._of_pauses,intonation_index,(voiced_syll_count)/(no_of_pause),TOEFL_Scale_Score,Score_Shannon_index,speaking_rate
+count,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0,520.0
+mean,0.8605969598692308,12.945962440311538,62.59323076923077,2.518096173119231,4.3634615384615385,107.19737200140385,371.57839859346154,0.9659444261788462,0.8979752612153846,179.32638882584618,0.978774687823077,51.26266793944231,390.41902438096156,78.87338589573076,82.56153846153846,0.5911082448115386,2.4538511483,0.7152254128653847,134.49807692307692,25.05576923076923,7.221153846153846,10.666672346961539,22.15,2.8966384615384615,3.1307692307692307
+std,0.5182093241255592,10.5650594846985,40.72478269048824,0.22998667582582683,0.5273004818246455,22.45725606317618,20.15060548377844,0.12178670100504711,0.16454949501474603,34.237851329849164,0.11755351318944955,12.770571860248674,39.9339976895332,11.150162170924927,50.73019855863106,0.16179502674802976,0.2827764589763398,0.18815351287187568,94.07769508793068,15.411715302931972,1.6929909389163906,10.532270288665403,4.960013518534626,0.6481826855860794,0.7333346807322868
+min,0.32,2.261335451,7.54,1.5615067480000002,3.0,28.00108004,327.06,0.7150403790000001,0.522027013,95.50871262,0.6422109810000001,14.39604874,192.0464154,60.61750438,3.0,0.066666667,1.570231608,0.39404583299999996,15.0,1.0,4.0,1.625,9.0,1.178,1.0
+25%,0.64127125825,6.6551681055,25.3825,2.3865753339999998,4.0,94.94677548749999,358.26271027499996,0.8927416985,0.80304569275,164.09509022499998,0.910213274,43.030803275,384.07417000000004,72.409799585,38.0,0.46666666700000003,2.25561121525,0.5940275525000001,51.75,12.0,6.0,6.53629032275,19.0,2.48575,3.0
+50%,0.7361035515000001,9.508095238,52.54,2.529843843,4.0,110.79772215,377.0716721,0.954491985,0.8861156294999999,182.5069874,0.969493785,52.38127351,399.6276496,79.045860065,75.0,0.583333333,2.4608981455,0.685492004,107.5,22.0,7.0,8.625,22.0,2.93,3.0
+75%,0.85710545775,15.0387528375,93.2025,2.65602008775,5.0,121.921153725,388.01647427500006,1.02866088675,1.012162024,198.4087777,1.0409318225000002,60.693097825,418.4163125,80.3394204525,119.0,0.7158961595,2.6453157129999996,0.79934069075,194.75,36.0,9.0,11.887500002500001,26.0,3.385,4.0
+max,4.689212121000001,92.25333333,181.83,3.3529533639999998,6.0,190.560794,399.6609917,1.427151945,1.442502751,313.60393860000005,1.473006332,84.0325436,424.380037,179.83311369999998,304.0,0.970588235,3.6152396330000003,2.107762509,403.0,93.0,10.0,125.5,29.0,3.96,6.0