aruno14 / speechrecognition Goto Github PK
View Code? Open in Web Editor NEWSpeech recognition system implemented using tensorflow
Speech recognition system implemented using tensorflow
Can i adjust for italian?
Hey first of all nice job!
But I have a question: Is the model trained with the Common Voice Set or the few words which are written in the test_voice.py file?
Is there one method for training, so could I start only this method and the rest is fininished by itself or what do I have to to reach this goal?
I had a similar issue to this and the listed solution helped:
tensorflow/tensorflow#2117
Added this before model generation.
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth = True
session = tf.compat.v1.Session(config=config)
Hi, I am having trouble extracting the very big 60 GB tar file, because the clips folder is huge. I was wondering what tool you used to extract because every time I do it the time increases exponentially.
Hi,
thanks for your tutorial :)
Im trying to run sentence.py with my dataset but it wont run on TF 11 on Python 3.6.
I couldnt yet figure out the cause :/
Could you please give me a helping hand?
Thanks!
sentence.py:122: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
return [np.array(batch_x_voice), np.array(batch_x_string)], np.array(batch_y_string)
Traceback (most recent call last):
File "sentence.py", line 161, in
model.fit(MySequence(X_voice, X_string, Y_string, batch_size), epochs=epochs, steps_per_epoch=len(X_string)//batch_size)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 1064, in fit
steps_per_execution=self._steps_per_execution)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 1112, in init
model=model)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 909, in init
**kwargs)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 781, in init
peek = _process_tensorlike(peek)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 1016, in _process_tensorlike
inputs = nest.map_structure(_convert_numpy_and_scipy, inputs)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/util/nest.py", line 659, in map_structure
structure[0], [func(*x) for x in entries],
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/util/nest.py", line 659, in
structure[0], [func(*x) for x in entries],
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 1011, in _convert_numpy_and_scipy
return ops.convert_to_tensor_v2_with_dispatch(x, dtype=dtype)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1405, in convert_to_tensor_v2_with_dispatch
value, dtype=dtype, dtype_hint=dtype_hint, name=name)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1415, in convert_to_tensor_v2
as_ref=False)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/profiler/trace.py", line 163, in wrapped
return func(*args, **kwargs)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1540, in convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/tensor_conversion_registry.py", line 52, in _default_conversion_function
return constant_op.constant(value, dtype, name=name)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 265, in constant
allow_broadcast=True)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 276, in _constant_impl
return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 301, in _constant_eager_impl
t = convert_to_eager_tensor(value, ctx, dtype)
File "/home/semir/keras_tf/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py", line 98, in convert_to_eager_tensor
return ops.EagerTensor(value, ctx.device_name, dtype)
ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray).
Also the startup:
2021-02-26 11:41:27.372359: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
voice_max_length: 200
2021-02-26 11:41:28.241010: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-26 11:41:28.241466: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-02-26 11:41:28.278295: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.278646: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.665GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2021-02-26 11:41:28.278677: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-02-26 11:41:28.280171: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-02-26 11:41:28.280215: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-02-26 11:41:28.280833: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-26 11:41:28.280985: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-26 11:41:28.282578: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-26 11:41:28.282962: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-02-26 11:41:28.283060: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-02-26 11:41:28.283147: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.283502: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.283822: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-02-26 11:41:28.284033: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-02-26 11:41:28.284237: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-26 11:41:28.284307: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.284618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.665GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2021-02-26 11:41:28.284645: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-02-26 11:41:28.284655: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-02-26 11:41:28.284664: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-02-26 11:41:28.284671: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-26 11:41:28.284679: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-26 11:41:28.284687: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-26 11:41:28.284694: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-02-26 11:41:28.284701: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-02-26 11:41:28.284732: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.285053: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.285365: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-02-26 11:41:28.285396: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-02-26 11:41:28.624714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-02-26 11:41:28.624736: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
2021-02-26 11:41:28.624741: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
2021-02-26 11:41:28.624853: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.625217: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.625540: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-26 11:41:28.625850: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10029 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
2021-02-26 11:41:28.837430: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
(612, 6, 513)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.