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当我尝试运行 pythontranscriber.py 时，它失败并出现以下错误：

Traceback (most recent call last):
  File "PythonTranscriber.py", line 14, in <module>
  from edu.cmu.sphinx.decoder import Decoder
  ImportError: No module named edu

我的脚本 PythonTranscriber.py：

import sys

libDir = "/home/karen/sphinx4-1.0beta5-scr/sphinx4-1.0beta5/src/sphinx4/" 
classPaths = [
    "sphinx4.jar",
    "jsapi.jar" ] 
for classPath in classPaths:
    sys.path.append(libDir + classPath)

true = 1 
false = 0

from edu.cmu.sphinx.decoder import Decoder 
from edu.cmu.sphinx.decoder import ResultListener 
from edu.cmu.sphinx.decoder.pruner import SimplePruner 
from edu.cmu.sphinx.decoder.scorer import ThreadedAcousticScorer 
from edu.cmu.sphinx.decoder.search import PartitionActiveListFactory 
from edu.cmu.sphinx.decoder.search import SimpleBreadthFirstSearchManager 
from edu.cmu.sphinx.frontend import DataBlocker 
from edu.cmu.sphinx.frontend import FrontEnd 
from edu.cmu.sphinx.frontend.endpoint import NonSpeechDataFilter 
from edu.cmu.sphinx.frontend.endpoint import SpeechClassifier 
from edu.cmu.sphinx.frontend.endpoint import SpeechMarker 
from edu.cmu.sphinx.frontend.feature import DeltasFeatureExtractor 
from edu.cmu.sphinx.frontend.feature import LiveCMN 
from edu.cmu.sphinx.frontend.filter import Preemphasizer 
from edu.cmu.sphinx.frontend.frequencywarp import MelFrequencyFilterBank 
from edu.cmu.sphinx.frontend.transform import DiscreteCosineTransform 
from edu.cmu.sphinx.frontend.transform import DiscreteFourierTransform 
from edu.cmu.sphinx.frontend.util import AudioFileDataSource 
from edu.cmu.sphinx.frontend.window import RaisedCosineWindower 
from edu.cmu.sphinx.instrumentation import BestPathAccuracyTracker 
from edu.cmu.sphinx.instrumentation import MemoryTracker 
from edu.cmu.sphinx.instrumentation import SpeedTracker 
from edu.cmu.sphinx.jsapi import JSGFGrammar 
from edu.cmu.sphinx.linguist.acoustic import UnitManager 
from edu.cmu.sphinx.linguist.acoustic.tiedstate import Sphinx3Loader 
from edu.cmu.sphinx.linguist.acoustic.tiedstate import TiedStateAcousticModel 
from edu.cmu.sphinx.linguist.dictionary import FastDictionary 
from edu.cmu.sphinx.linguist.flat import FlatLinguist 
from edu.cmu.sphinx.recognizer import Recognizer 
from edu.cmu.sphinx.util import LogMath 
from java.util.logging import Logger 
from java.util.logging import Level 
from java.net import URL 
from java.util import ArrayList

# if (args.length < 1) {
#  throw new Error("USAGE: GroovyTranscriber <sphinx4 root> [<WAV file>]")
# }

root = "../../.."

# init common  
Logger.getLogger("").setLevel(Level.WARNING) 
logMath = LogMath(1.0001, true) 
absoluteBeamWidth = -1 
relativeBeamWidth = 1E-80 
wordInsertionProbability = 1E-36 
languageWeight = 8.0

# init audio data 
audioSource = AudioFileDataSource(3200, None) 
audioURL =  URL("file:" + root + "/src/apps/edu/cmu/sphinx/demo/transcriber/10001-90210-01803.wav")

# (args.length > 1) ?
#  File(args[0]).toURI().toURL() :   audioSource.setAudioFile(audioURL, None)

# init front end 
dataBlocker = DataBlocker(
        10 # blockSizeMs ) speechClassifier = SpeechClassifier(
        10,     # frameLengthMs,
        0.003, # adjustment,
        10,     # threshold,
        0       # minSignal 
)

speechMarker = SpeechMarker(
        200, # startSpeechTime,
        500, # endSilenceTime,
        100, # speechLeader,
        50,  # speechLeaderFrames
        100  # speechTrailer 
)

nonSpeechDataFilter = NonSpeechDataFilter()

premphasizer = Preemphasizer(
        0.97 # preemphasisFactor 
) 
windower = RaisedCosineWindower(
        0.46, # double alpha
        25.625, # windowSizeInMs
        10.0 # windowShiftInMs 
) 
fft = DiscreteFourierTransform(
        -1, # numberFftPoints
        false # invert 
) 
melFilterBank = MelFrequencyFilterBank(
        130.0, # minFreq,
        6800.0, # maxFreq,
        40 # numberFilters 
) 
dct = DiscreteCosineTransform(
        40, # numberMelFilters,
        13  # cepstrumSize 
) 
cmn = LiveCMN(
        12.0, # initialMean,
        100,  # cmnWindow,
        160   # cmnShiftWindow 
) 
featureExtraction = DeltasFeatureExtractor(
        3 # window 
)

pipeline = [
        audioSource,
        dataBlocker,
        speechClassifier,
        speechMarker,
        nonSpeechDataFilter,
        premphasizer,
        windower,
        fft,
        melFilterBank,
        dct,
        cmn,
        featureExtraction ]

frontend = FrontEnd(pipeline)

# init models 
unitManager = UnitManager()

modelLoader = Sphinx3Loader(
        "file:" + root + "/models/acoustic/tidigits/model.props",
        logMath,
        unitManager,
        true,
        true,
        39,
        "file:" + root + "/models/acoustic/tidigits/wd_dependent_phone.500.mdef",
        "file:" + root + "/models/acoustic/tidigits/wd_dependent_phone.cd_continuous_8gau/",
        0.0,
        1e-7,
        0.0001,
        true)

model = TiedStateAcousticModel(modelLoader, unitManager, true)

dictionary = FastDictionary(
        URL("file:" + root + "/models/acoustic/tidigits/dictionary"),
        URL("file:" + root + "/models/acoustic/tidigits/fillerdict"),
        ArrayList(),
        false,
        "<sil>",
        false,
        false,
        unitManager)

# init linguist 
grammar = JSGFGrammar(
        # URL baseURL,
        URL("file:" + root + "/src/apps/edu/cmu/sphinx/demo/transcriber/"),
        logMath, # LogMath logMath,
        "digits", # String grammarName,
        false, # boolean showGrammar,
        false, # boolean optimizeGrammar,
        false, # boolean addSilenceWords,
        false, # boolean addFillerWords,
        dictionary # Dictionary dictionary 
)

linguist = FlatLinguist(
        model, # AcousticModel acousticModel,
        logMath, # LogMath logMath,
        grammar, # Grammar grammar,
        unitManager, # UnitManager unitManager,
        wordInsertionProbability, # double wordInsertionProbability,
        1.0, # double silenceInsertionProbability,
        1.0, # double fillerInsertionProbability,
        1.0, # double unitInsertionProbability,
        languageWeight, # float languageWeight,
        false, # boolean dumpGStates,
        false, # boolean showCompilationProgress,
        false, # boolean spreadWordProbabilitiesAcrossPronunciations,
        false, # boolean addOutOfGrammarBranch,
        1.0, # double outOfGrammarBranchProbability,
        1.0, # double phoneInsertionProbability,
        None # AcousticModel phoneLoopAcousticModel 
)

# init recognizer 
scorer = ThreadedAcousticScorer(frontend, None, 10, true, 0)

pruner = SimplePruner()

activeListFactory = PartitionActiveListFactory(absoluteBeamWidth, relativeBeamWidth, logMath)

searchManager = SimpleBreadthFirstSearchManager(
        logMath, linguist, pruner,
        scorer, activeListFactory,
        false, 0.0, 0, false)

decoder = Decoder(searchManager,
        false, false,
        ArrayList(),
        100000)

recognizer = Recognizer(decoder, None)

# allocate the resourcs necessary for the recognizer recognizer.allocate()

# Loop unitl last utterance in the audio file has been decoded, in which case the recognizer will return None. 
result = recognizer.recognize() 
while (result != None):
    resultText = result.getBestResultNoFiller()
    print resultText
    result = recognizer.recognize()

我已经安装了 Jython！

请帮我！

4

1 回答 1

1

要加载 Java 代码，请尝试将 jar 添加到您的classpath。

如果您不熟悉如何执行此操作，请使用

 export CLASSPATH=$CLASSPATH:/path/to/sphinx4.jar:/path/jsapi.jar

或者将其添加到您的命令行脚本中：

java -cp /path/to/jars -jar /home/karen/jython-installer-2.5.3/jython.jar PythonTranscriber.py

编辑：

  1. 因此，我按照此处的说明下载并安装了 Sphinx-4。jar 文件的路径与您在脚本中的路径不同。他们在sphinx4/lib目录下。您可能需要仔细检查路径的正确性。

  2. 我按如下方式运行了您的脚本（已修改，但没有重大更改）：

    import sys,os
lib_dir = '/home/.../jars/sphinx4/lib/'
classpaths = [ 'sphinx4.jar', 'jsapi.jar' ]
for cp in classpaths:
    sys.path.append(os.path.join(lib_dir,cp))

from edu.cmu.sphinx.decoder import Decoder
from ... import ...
etc.
from java.util import ArrayList

    使用命令：

    jython python_transcriber.py

  3. 这几乎奏效了，除了您还有一个导入错误：

    from edu.cmu.sphinx.jsapi import JSGFGrammar

    根据javadoc，应该是：

    from edu.cmu.sphinx.jsgf import JSGFGrammar

这为我解决了。没有尝试其余代码，但至少所有导入都有效。

于 2012-11-13T19:01:35.940 回答