speech recognition demo in python
git-svn-id: http://svn.freeswitch.org/svn/freeswitch/trunk@5659 d0543943-73ff-0310-b7d9-9358b9ac24b2
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Traun Leyden
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# empty
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from freeswitch import *
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from xml.dom import minidom
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VOICE_ENGINE = "cepstral"
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VOICE = "William"
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"""
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A few classes that make it easier to write speech applications
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using Python. It is roughly modelled after the equivalent that
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is written in JavaScript.
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Status: should work, but not yet complete. some pending items
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are mentioned in comments
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"""
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class Grammar:
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def __init__(self, name, path, obj_path,
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min_score=1, confirm_score=400, halt=False):
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"""
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@param name - name of grammar to reference it later
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@param path - path to xml grammar file
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@param obj_path - xml path to find interpretation from root
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in result xml, eg, 'interpretation'
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@param min_score - score threshold to accept result
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@param confirm_score - if score below this threshold, ask user
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if they are sure this is correct
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@param halt - not sure what was used for in js, currently unused
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"""
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self.name=name
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self.path=path
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self.obj_path=obj_path
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self.min_score=min_score
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self.confirm_score=confirm_score
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self.halt=halt
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class SpeechDetect:
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def __init__(self, session, module_name, ip_addr):
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self.session=session
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self.module_name=module_name
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self.ip_addr=ip_addr
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self.grammars = {}
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def addGrammar(self, grammar):
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self.grammars[grammar.name]=grammar
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def setGrammar(self, name):
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self.grammar = self.grammars[name]
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def detectSpeech(self):
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# TODO: we might not always want to call detect_speech
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# with this cmd, see js version for other options
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# also see detect_speech_function() in mod_dptools.c
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cmd = "%s %s %s %s" % (self.module_name,
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self.grammar.name,
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self.grammar.path,
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self.ip_addr)
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console_log("debug", "calling detect_speech with: %s\n" % cmd)
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self.session.execute("detect_speech", cmd)
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console_log("debug", "finished calling detect_speech\n")
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class SpeechObtainer:
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def __init__(self, speech_detect, required_phrases, wait_time, max_tries):
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"""
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@param speech_detect - the speech detect object, which holds a
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reference to underlying session and can
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be re-used by many SpeechObtainers
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@param required_phrases - the number of required phrases from the
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grammar. for example if its prompting for
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the toppings on a sandwhich and min toppings
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is 3, use 3. normally will be 1.
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@param wait_time - the time, in millisconds, to wait for
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input during each loop iteration
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@param max_tries - this number multiplied by wait time gives the
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'total wait time' before we give up and return
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partial or no result
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"""
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self.speech_detect=speech_detect
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self.required_phrases=required_phrases
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self.wait_time=wait_time
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self.max_tries=max_tries
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self.detected_phrases = []
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def setGrammar(self, grammar):
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"""
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@param grammar - instance of grammar class
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"""
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self.grammar=grammar
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self.speech_detect.addGrammar(grammar)
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self.speech_detect.setGrammar(self.grammar.name)
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def detectSpeech(self):
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self.speech_detect.detectSpeech()
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def run(self):
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"""
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start speech detection with the current grammar,
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and listen for results from asr engine. once a result
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has been returned, return it to caller
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"""
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def dtmf_handler(input, itype, funcargs):
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console_log("INFO","\n\nDTMF itype: %s\n" % itype)
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if itype == 1: # TODO!! use names for comparison instead of number
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return self.handle_event(input, funcargs)
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elif itype== 0:
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console_log("INFO","\n\nDTMF input: %s\n" % input)
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else:
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console_log("INFO","\n\nUnknown input type: %s\n" % itype)
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return None
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num_tries = 0
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session = self.speech_detect.session
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console_log("debug", "setting dtmf callback\n")
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session.setDTMFCallback(dtmf_handler, "")
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console_log("debug", "calling getDigits\n")
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console_log("debug", "starting run() while loop\n")
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while (session.ready() and
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num_tries < self.max_tries and
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len(self.detected_phrases) < self.required_phrases):
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console_log("debug", "top of run() while loop\n")
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session.collectDigits(self.wait_time)
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num_tries += 1
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console_log("debug", "while loop finished\n")
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return self.detected_phrases
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def handle_event(self, event, funcargs):
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"""
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when the dtmf handler receives an event, it calls back
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this method. event is a dictionary with subdictionaries ..
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Example 1
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=========
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{'body': None, 'headers': {'Speech-Type': 'begin-speaking'}}
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Example 2
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=========
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{'body': '<result xmlns='http://www.ietf.org/xml/ns/mrcpv2'
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xmlns:ex='http://www.example.com/example' score='100'
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grammar='session:request1@form-level.store'><interpretation>
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<input mode='speech'>waffles</input></interpretation></result>',
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'headers': {'Speech-Type': 'detected-speech'}}
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This dictionary is constructed in run_dtmf_callback() in
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freeswitch_python.cpp
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"""
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# what kind of event?
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headers = event['headers']
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speech_type = headers['Speech-Type']
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if speech_type == "begin-speaking":
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# not sure what to do with this, try returning "stop"
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# so that it might stop playing a sound file once
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# speech has been detected
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return "stop"
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elif speech_type == "detected-speech":
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# extract the detected phrase. from result
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# BUG: this assumes only ONE interpretation in the xml
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# result. rest will get igored
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# NOTE: have to wrap everything with str() (at least
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# calls to console_log because otherwise it chokes on
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# unicode strings.
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# TODO: check the score
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body = event['body']
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dom = minidom.parseString(body)
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phrase = dom.getElementsByTagName(self.grammar.obj_path)[0]
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phrase_text = self.getText(phrase)
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if phrase_text:
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self.detected_phrases.append(str(phrase_text))
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# do we want to return stop? what should we return?
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return "stop"
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else:
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raise Exception("Unknown speech event: %s" % speech_type)
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def getText(self, elt):
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""" given an element, get its text. if there is more than
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one text node child, just append all the text together.
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"""
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result = ""
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children = elt.childNodes
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for child in children:
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if child.nodeType == child.TEXT_NODE:
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result += str(child.nodeValue)
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return result
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from freeswitch import *
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from py_modules.speechtools import Grammar, SpeechDetect
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from py_modules.speechtools import SpeechObtainer
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import time, os
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VOICE_ENGINE = "cepstral"
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VOICE = "William"
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GRAMMAR_ROOT = "/usr/src/freeswitch_trunk/scripts"
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"""
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Example speech recognition application in python.
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How to make this work:
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* Get mod_openmrcp working along with an MRCP asr server
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* Add /usr/src/freeswitch/scripts or equivalent to your PYTHONPATH
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* Restart freeswitch
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* Create $GRAMMAR_ROOT/mainmenu.xml from contents in mainmenu() comments
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"""
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class RecipeWizard:
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def __init__(self, session):
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self.session=session
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self.session.set_tts_parms(VOICE_ENGINE, VOICE)
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self.main()
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def main(self):
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console_log("debug", "recipe wizard main()\n")
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self.speechdetect = SpeechDetect(self.session, "openmrcp", "127.0.0.1");
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self.speechobtainer = SpeechObtainer(speech_detect=self.speechdetect,
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required_phrases=1,
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wait_time=5000,
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max_tries=3)
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gfile = os.path.join(GRAMMAR_ROOT, "mainmenu.xml")
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self.grammar = Grammar("mainmenu", gfile,"input",80,90)
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self.speechobtainer.setGrammar(self.grammar);
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console_log("debug", "calling speechobtainer.run()\n")
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self.speechobtainer.detectSpeech()
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self.session.speak("Hello. Welcome to the recipe wizard. Drinks or food?")
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result = self.speechobtainer.run()
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console_log("debug", "speechobtainer.run() result: %s\n" % result)
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if result:
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self.session.speak("Received result. Result is: %s" % result[0])
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else:
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self.session.speak("Sorry, I did not hear you")
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console_log("debug", "speechobtainer.run() finished\n")
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def mainmenu():
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"""
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<!DOCTYPE grammar PUBLIC "-//W3C//DTD GRAMMAR 1.0//EN"
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"http://www.w3.org/TR/speech-grammar/grammar.dtd">
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<grammar xmlns="http://www.w3.org/2001/06/grammar" xml:lang="en"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://www.w3.org/2001/06/grammar
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http://www.w3.org/TR/speech-grammar/grammar.xsd"
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version="1.0" mode="voice" root="root">
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<rule id="root" scope="public">
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<rule id="main">
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<one-of>
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<item weight="10">drinks</item>
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<item weight="2">food</item>
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</one-of>
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</rule>
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</rule>
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</grammar>
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"""
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pass
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def handler(uuid):
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session = PySession(uuid)
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session.answer()
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rw = RecipeWizard(session)
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session.hangup("1")
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