CODEWITHSUNDEEP
pythonpython-2.7numpyscipyspeech-recognition
OBX
OBX

Reputation: 6114

TypeError: 'float' object cannot be interpreted as an index, possible way to resolve this?

Trying to build a speaker recognition project using Python 2.x . As dependency, the project relies on scipy and numpy. However when the code is executed the stack trace generated is : 

  Traceback (most recent call last):
  File "../python/raw2ivec.py", line 227, in <module>
    USEHAMMING  = True)
  File "/Users/shaheenakader/Downloads/vbs_demo/python/features.py", line 108, in mfcc_htk
    x = framing(x.astype("float"), window.size, window.size-noverlap).copy()
  File "/Users/shaheenakader/Downloads/vbs_demo/python/features.py", line 14, in framing
    return np.lib.stride_tricks.as_strided(a, shape=shape, strides=strides)
  File "/Users/shaheenakader/anaconda2/envs/voicebio/lib/python2.7/site-packages/numpy/lib/stride_tricks.py", line 102, in as_strided
    array = np.asarray(DummyArray(interface, base=x))
  File "/Users/shaheenakader/anaconda2/envs/voicebio/lib/python2.7/site-packages/numpy/core/numeric.py", line 501, in asarray
    return array(a, dtype, copy=False, order=order)
    TypeError: 'float' object cannot be interpreted as an index

I tried existing solutions to similar questions:

However, couldn't help to resolve the issue.

The relevant code snippets associated with respective files have been added below:

raw2ivec.py

    print '  Extracting features',
    fea = features.mfcc_htk(sig, 
                            window      = WINDOWSIZE/SOURCERATE,
                            noverlap    = (WINDOWSIZE-TARGETRATE)/SOURCERATE,
                            fbank_mx    = fbank_mx,
                            _0          = 'first',
                            NUMCEPS     = NUMCEPS,
                            RAWENERGY   = RAWENERGY,
                            PREEMCOEF   = PREEMCOEF,
                            CEPLIFTER   = CEPLIFTER,
                            ZMEANSOURCE = ZMEANSOURCE,
                            ENORMALISE  = ENORMALISE,
                            ESCALE      = 0.1,
                            SILFLOOR    = 50.0,
                            USEHAMMING  = True)

    print '[n=' + repr(len(fea)) + ' frames]'

    print '  Adding derivatives'
    # [add_deriv] step 
    fea = features.add_deriv(fea,(deltawindow,accwindow))

features.py

def mfcc_htk(x, window, noverlap, fbank_mx, nfft=None,
         _0="last", _E=None, NUMCEPS=12,
         USEPOWER=False, RAWENERGY=True, PREEMCOEF=0.97, CEPLIFTER=22.0, ZMEANSOURCE=False,
         ENORMALISE=True, ESCALE=0.1, SILFLOOR=50.0, USEHAMMING=True):
"""MFCC Mel Frequency Cepstral Coefficients
Returns NUMCEPS-by-M matrix of MFCC coeficients extracted form signal x,
where M is the number of extracted frames, which can be computed as
floor((length(x)-noverlap)/(window-noverlap)). Remaining parameters
have the following meaning:
x         - input signal
window    - frame window lentgth (in samples, i.e. WINDOWSIZE/SOURCERATE) 
            or vector of widow weights override default windowing function
            (see option USEHAMMING)
noverlap  - overlapping between frames (in samples, i.e window-TARGETRATE/SOURCERATE)
fbank_mx  - array with (Mel) filter bank (as returned by function mel_fbank_mx()).
            Note that this must be compatible with the parameter 'nfft'.
nfft      - number of samples for FFT computation. By default, it is  set in the
            HTK-compatible way to the window length rounded up to the next higher
            pover of two.
_0, _E    - include C0 or/and energy as the "first" or the "last" coefficient(s)
            of each feature vector. The possible values are: "first", "last", None.
            If both C0 and energy are used, energy will be the very first or the
            very last coefficient.

Remaining options have exactly the same meaning as in HTK.

See also:
  mel_fbank_mx:
      to obtain the matrix for the parameter fbank_mx
  add_deriv: 
      for adding delta, double delta, ... coefficients
  add_dither:
      for adding dithering in HTK-like fashion
"""

dct_mx = dct_basis(NUMCEPS+1,fbank_mx.shape[1]).T
dct_mx[:,0] = np.sqrt(2.0/fbank_mx.shape[1])
if type(USEPOWER) == bool:
    USEPOWER += 1
if np.isscalar(window):
    window = np.hamming(window) if USEHAMMING else np.ones(window)
if nfft is None:
    nfft = 2**int(np.ceil(np.log2(window.size)))
x = framing(x.astype("float"), window.size, window.size-noverlap).copy()
#^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - - - - SUSPECTED LINE WHERE ERROR IS CAUSED
if ZMEANSOURCE:
    x -= x.mean(axis=1)[:,np.newaxis]
if _E is not None and RAWENERGY:
    energy = np.log((x**2).sum(axis=1))
if PREEMCOEF is not None:
    x = preemphasis(x, PREEMCOEF)
x *= window
if _E is not None and not RAWENERGY:
    energy = np.log((x**2).sum(axis=1))
#x = np.abs(scipy.fftpack.fft(x, nfft))
#x = x[:,:x.shape[1]/2+1]
x = np.abs(np.fft.rfft(x, nfft))
x = np.log(np.maximum(1.0, (x**USEPOWER).dot(fbank_mx))).dot(dct_mx)
if CEPLIFTER is not None and CEPLIFTER > 0:
    x *= 1.0 + 0.5 * CEPLIFTER * np.sin(np.pi * np.arange(NUMCEPS+1) / CEPLIFTER)
if _E is not None and ENORMALISE:
    energy = (energy - energy.max())       * ESCALE + 1.0
    min_val  = -np.log(10**(SILFLOOR/10.)) * ESCALE + 1.0
    energy[energy < min_val] = min_val

return np.hstack(([energy[:,np.newaxis]] if _E == "first" else []) +
                 ([x[:,:1]]              if _0 == "first" else []) +
                  [x[:,1:]] +
                 ([x[:,:1]]              if (_0 in ["last", True])  else []) +
                 ([energy[:,np.newaxis]] if (_E in ["last", True])  else []))

def framing(a, window, shift=1):
shape = ((a.shape[0] - window) / shift + 1, window) + a.shape[1:]
strides = (a.strides[0]*shift,a.strides[0]) + a.strides[1:]
return np.lib.stride_tricks.as_strided(a, shape=shape, strides=strides)

What is possibly causing the issue, and what's the best way to fix this? Any help would be much appreciated.

Upvotes: 2

Views: 484

Answers (2)

Bob
Bob

Reputation: 14654

If you want to fix the code, change the framing function to use integer multiplication, this was changed from python2 to python3.

def framing(a, window, shift=1):
    shape = ((a.shape[0] - window) // shift + 1, window) + a.shape[1:]
    strides = (a.strides[0]*shift,a.strides[0]) + a.strides[1:]
    return np.lib.stride_tricks.as_strided(a, shape=shape, strides=strides)

Upvotes: 1

AneesAhmed777
AneesAhmed777

Reputation: 2695

You didn't link the project, but here it is for others: https://www.voicebiometry.org/

I was also trying to work on it and encountered the same error.

This project was last updated in 2015, and the error looked to me more like an API error than math error. So I had a hunch that if I installed the versions of numpy and scipy from 2015, the project would work. As you can see in the release history of numpy and scipy on PYPI, the last version that was released in 2015 was 1.10.2 for numpy and 0.16.1 for scipy.

So install them using these commands

pip install numpy==1.10.2
pip install scipy==0.16.1

Now, the original project code works just fine!

Upvotes: 0

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