Port 2021.1 documentation updates for GNA plugin and speech libs and demos. (#2564)

* Update docs for speech libs and demos (#2518)

* [GNA] Documentation updates for 2021.1 (#2460)

* [GNA] Documentation updates for 2021.1

* Take Mike's comments into account

* More fixes according to review

* Fix processor generation names

docs/IE_DG/supported_plugins/GNA.md

@@ -19,7 +19,7 @@ Devices with Intel® GNA support:
 
 * [Amazon Alexa* Premium Far-Field Developer Kit](https://developer.amazon.com/en-US/alexa/alexa-voice-service/dev-kits/amazon-premium-voice)
 
-* [Gemini Lake](https://ark.intel.com/content/www/us/en/ark/products/codename/83915/gemini-lake.html):
+* [Intel® Pentium® Silver Processors N5xxx, J5xxx and Intel® Celeron® Processors N4xxx, J4xxx](https://ark.intel.com/content/www/us/en/ark/products/codename/83915/gemini-lake.html):
 	- Intel® Pentium® Silver J5005 Processor
 	- Intel® Pentium® Silver N5000 Processor
 	- Intel® Celeron® J4005 Processor
@@ -27,10 +27,10 @@ Devices with Intel® GNA support:
 	- Intel® Celeron® Processor N4100
 	- Intel® Celeron® Processor N4000
 
-* [Cannon Lake](https://ark.intel.com/content/www/us/en/ark/products/136863/intel-core-i3-8121u-processor-4m-cache-up-to-3-20-ghz.html):
+* [Intel® Core™ Processors (formerly codenamed Cannon Lake)](https://ark.intel.com/content/www/us/en/ark/products/136863/intel-core-i3-8121u-processor-4m-cache-up-to-3-20-ghz.html):
 Intel® Core™ i3-8121U Processor
 
-* [Ice Lake](https://ark.intel.com/content/www/us/en/ark/products/codename/74979/ice-lake.html):
+* [10th Generation Intel® Core™ Processors (formerly codenamed Ice Lake)](https://ark.intel.com/content/www/us/en/ark/products/codename/74979/ice-lake.html):
 	- Intel® Core™ i7-1065G7 Processor
 	- Intel® Core™ i7-1060G7 Processor
 	- Intel® Core™ i5-1035G4 Processor
@@ -42,6 +42,8 @@ Intel® Core™ i3-8121U Processor
 	- Intel® Core™ i3-1000G1 Processor
 	- Intel® Core™ i3-1000G4 Processor
 
+* All [11th Generation Intel® Core™ Processors (formerly codenamed Tiger Lake)](https://ark.intel.com/content/www/us/en/ark/products/codename/88759/tiger-lake.html).
+
 > **NOTE**: On platforms where Intel® GNA is not enabled in the BIOS, the driver cannot be installed, so the GNA plugin uses the software emulation mode only.
 
 ## Drivers and Dependencies
@@ -64,10 +66,11 @@ The list of supported layers can be found
 [here](Supported_Devices.md) (see the GNA column of Supported Layers section).
 Limitations include:
 
-- Only 1D convolutions (in the models converted from [Kaldi](../../MO_DG/prepare_model/convert_model/Convert_Model_From_Kaldi.md) framework) are natively supported
+- Only 1D convolutions are natively supported in the models converted from:
+	- [Kaldi](../../MO_DG/prepare_model/convert_model/Convert_Model_From_Kaldi.md) framework;
+	- [TensorFlow](../../MO_DG/prepare_model/convert_model/Convert_Model_From_TensorFlow.md) framework; note that for TensorFlow models, the option `--disable_nhwc_to_nchw` must be used when running the Model Optimizer.
 - The number of output channels for convolutions must be a multiple of 4
 - Permute layer support is limited to the cases where no data reordering is needed, or when reordering is happening for 2 dimensions, at least one of which is not greater than 8
-- Power layer only supports the power parameter equal to 1
 
 #### Experimental Support for 2D Convolutions
 
@@ -159,6 +162,30 @@ Heterogeneous plugin was tested with the Intel® GNA as a primary device and
 
 > **NOTE:** Due to limitation of the Intel® GNA backend library, heterogenous support is limited to cases where in the resulted sliced graph, only one subgraph is scheduled to run on GNA\_HW or GNA\_SW devices.
 
+## Recovery from interruption by high-priority Windows audio processes\*
+
+As noted in the introduction, GNA is designed for real-time workloads such as noise reduction.
+For such workloads, processing should be time constrained, otherwise extra delays may cause undesired effects such as
+audio "glitches". To make sure that processing can satisfy real time requirements, the GNA driver provides a QoS
+(Quality of Service) mechanism which interrupts requests that might cause high-priority Windows audio processes to miss
+schedule, thereby causing long running GNA tasks to terminate early.
+
+Applications should be prepared for this situation.
+If an inference (in `GNA_HW` mode) cannot be executed because of such an interruption, then `InferRequest::Wait()` will return status code
+`StatusCode::INFER_NOT_STARTED` (note that it will be changed to a more meaningful status code in future releases).
+
+Any application working with GNA must properly react if it receives this code. Various strategies are possible.
+One of the options is to immediately switch to GNA SW emulation mode:
+
+```cpp
+std::map<std::string, Parameter> newConfig;
+newConfig[GNAConfigParams::KEY_GNA_DEVICE_MODE] = Parameter("GNA_SW_EXACT");
+executableNet.SetConfig(newConfig);
+
+```
+
+then resubmit and switch back to GNA_HW after some time hoping that the competing application has finished.
+
 ## See Also
 
 * [Supported Devices](Supported_Devices.md)

docs/IE_DG/supported_plugins/Supported_Devices.md

@@ -94,7 +94,7 @@ the supported output precision  depends on the actual underlying devices. _Gener
 |GPU plugin    |Supported     |Supported     |Supported     |Supported     |
 |FPGA plugin   |Not supported |Supported     |Supported     |Not supported |
 |VPU plugins   |Not supported |Supported     |Supported     |Supported     |
-|GNA plugin    |Not supported |Not supported |Not supported |Supported     |
+|GNA plugin    |Not supported |Supported     |Supported     |Supported     |
 
 ### Supported Output Layout
 

inference-engine/samples/speech_libs_and_demos/Speech_libs_and_demos.md

@@ -1,7 +1,7 @@
 # Speech Library and Speech Recognition Demos {#openvino_inference_engine_samples_speech_libs_and_demos_Speech_libs_and_demos}
 
-Starting with the 2020.1 release, OpenVINO™ provides a set of libraries and demos to demonstrate end-to-end
-speech recognition, as well as new acoustic and language models that can work with these demos.
+Intel® distributions of OpenVINO™ toolkit for Linux* OS and Windows* OS provide a set of libraries and demos to
+demonstrate end-to-end speech recognition, as well as new acoustic and language models that can work with these demos.
 The libraries are designed for preprocessing (feature extraction) to get a feature vector from a speech signal, as well
 as postprocessing (decoding) to produce text from scores. Together with OpenVINO™-based neural-network speech recognition,
 these libraries provide an end-to-end pipeline converting speech to text. This pipeline is demonstrated by the
@@ -38,7 +38,7 @@ Additionally, [new acoustic and language models](http://download.01.org/opencv/2
 
 To download pretrained models and build all dependencies:
 
-* On Linux* OS or macOS*, use the shell script `<INSTALL_DIR>/deployment_tools/demo/demo_speech_recognition.sh`
+* On Linux* OS, use the shell script `<INSTALL_DIR>/deployment_tools/demo/demo_speech_recognition.sh`
 
 * On Windows* OS, use the batch file `<INSTALL_DIR>\deployment_tools\demo\demo_speech_recognition.bat`
 
@@ -51,7 +51,7 @@ The script follows the steps below:
 
 If you are behind a proxy, set the following environment variables in a console session before running the script:
 
-* On Linux* OS and macOS*:
+* On Linux* OS:
 
 ```sh
 export http_proxy=http://{proxyHost}:{proxyPort}