Я скачал код с https://github.com/prakashpandey9/IsolatedSpeechRecognition
Этот код был совместим с Python 2, и я написал его для Python 3.
Но я получаю эту ошибку:
~/Desktop/IsolatedSpeechRecognition-master $ python Isolated_Speech_Recognition.py
List of spoken words: ['dog', 'human', 'god', 'eye', 'book', 'fast', 'apple', 'cat']
{'book', 'human', 'fast', 'apple', 'god', 'cat', 'dog', 'eye'}
Number of total files: 120
Labels and label indices [6. 6. 6. 6. 6. 6. 6. 6. 6. 6. 6. 6. 6. 6. 6. 1. 1. 1. 1. 1. 1. 1. 1. 1.
1. 1. 1. 1. 1. 1. 4. 4. 4. 4. 4. 4. 4. 4. 4. 4. 4. 4. 4. 4. 4. 7. 7. 7.
7. 7. 7. 7. 7. 7. 7. 7. 7. 7. 7. 7. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 3. 3. 3. 3. 3. 3.
3. 3. 3. 3. 3. 3. 3. 3. 3. 5. 5. 5. 5. 5. 5. 5. 5. 5. 5. 5. 5. 5. 5. 5.]
(120, 3841)
Processed observation 0
Processed observation 10
Processed observation 20
Processed observation 30
Processed observation 40
Processed observation 50
Processed observation 60
Processed observation 70
Processed observation 80
Processed observation 90
Processed observation 100
Processed observation 110
(120, 7, 33)
Traceback (most recent call last):
File "Isolated_Speech_Recognition.py", line 269, in <module>
_ = [model.train(X_train[y_train == y, :, :]) for m, y in zip(ms, ys)]
File "Isolated_Speech_Recognition.py", line 269, in <listcomp>
_ = [model.train(X_train[y_train == y, :, :]) for m, y in zip(ms, ys)]
NameError: name 'model' is not defined
это фрагмент кода, в котором я получаю сообщение об ошибке:
from sklearn.model_selection import StratifiedShuffleSplit
sss = StratifiedShuffleSplit(test_size=0.1, random_state=0)
for n,i in enumerate(all_obs):
all_obs[n] /= all_obs[n].sum(axis=0)
for train_index, test_index in sss.split(all_obs, all_labels):
X_train, X_test = all_obs[train_index, ...], all_obs[test_index, ...]
y_train, y_test = all_labels[train_index], all_labels[test_index]
ys = set(all_labels)
ms = [gmmhmm(7) for y in ys]
_ = [model.train(X_train[y_train == y, :, :]) for m, y in zip(ms, ys)]
ps1 = [model.test(X_test) for m in ms]
res1 = np.vstack(ps1)
predicted_label1 = np.argmax(res1, axis=0)
dictionary = ['apple', 'banana', 'elephant', 'dog', 'frog', 'cat', 'jack', 'god', 'Intelligent', 'hello']
spoken_word = []
for i in predicted_label1:
spoken_word.append(dictionary[i])
print(spoken_word)
missed = (predicted_label1 != y_test)
print('Test accuracy: %.2f percent' % (100 * (1 - np.mean(missed))))
Я пытался, но не смог выяснить, почему я получаю эту ошибку и как ее устранить.