Cuestionario vinculado a una guía · Medio Nivel
Prueba ASR convolucional Wav2Letter
Evalúe el diseño acústico de wav2letter y el objetivo de ASG, con las diferencias entre los experimentos originales, las herramientas C++ posteriores y los campos receptivos.
Pregunta 1 de 8
Which architecture defines the original wav2letter acoustic network?
Vista previa de cada pregunta8 preguntas
Las respuestas y explicaciones aparecen a medida que realiza el cuestionario.
- Which architecture defines the original wav2letter acoustic network?
- A recurrent-only network
- A decision-tree ensemble
- A Gaussian-mixture-only acoustic network
- A convolutional network without recurrent acoustic connections
- Which research organization is associated with the original 2016 wav2letter paper?
- Google Cerebro
- Microsoft Investigación
- Facebook AI Research
- NVIDIA
- Which output representation does the original wav2letter acoustic model predict from its studied speech inputs?
- Only an intermediate human-labeled phoneme transcript
- Letters or graphemes
- Only a list of speaker names
- Only a global tempo value
- ¿En qué se diferencia la pérdida AutoSegCriterion (ASG) original de la pérdida CTC más común?
- Elimina el símbolo en blanco y modela las transiciones de letras directamente.
- Requiere alineación manual por cuadro
- Solo funciona con RNN
- No puede manejar secuencias de longitud variable.
- What computation difference does a convolutional acoustic stack offer compared with a conventional recurrent dependency across time?
- Every complete speech decoder becomes fully parallel
- No labeled transcription data is needed for its supervised objective
- Convolution operations can be evaluated across positions without that recurrent chain
- Every workload necessarily obtains zero transcription error
- Which C++ machine-learning library documents ASR applications formerly associated with the wav2letter project?
- scikit-learn only
- An audio-compression format
- A required spelling dictionary standard
- linterna
- Which tensor library does the later wav2letter++ paper identify for its C++ framework?
- ArrayFire
- A required Java virtual machine
- Only the original Torch7 runtime
- A fixed spreadsheet engine
- For two length-three temporal convolutions at stride one and dilation one with no padding or intervening operation, how many original positions can one second-layer output depend on?
- tres
- Cinco
- Seis
- Nueve