diff --git a/arm_compute/runtime/CL/functions/CLLSTMLayer.h b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
index 3add152..44b3baf 100644
--- a/arm_compute/runtime/CL/functions/CLLSTMLayer.h
+++ b/arm_compute/runtime/CL/functions/CLLSTMLayer.h
@@ -39,6 +39,7 @@
 #include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h"
 #include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
 #include "arm_compute/runtime/CL/functions/CLGEMM.h"
+#include "arm_compute/runtime/CL/functions/CLMeanStdDevNormalizationLayer.h"
 #include "arm_compute/runtime/IMemoryManager.h"
 #include "arm_compute/runtime/common/LSTMParams.h"
 
@@ -76,17 +77,22 @@
      * @param[out] output                      Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
      *                                         Data types supported: Same as @p input.
      * @param[in]  lstm_params                 (Optional) Weights tensors used in peephole optimization:
-     *                                         input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     *                                         recurrent_to_input_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     *                                         cell_to_input_weights        1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
-     *                                         cell_to_forget_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     *                                         cell_to_output_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     *                                         input_gate_bias              1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
-     *                                         projection_weights           2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     *                                         projection_bias              1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
+     *                                         input_to_input_weights         2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     *                                         recurrent_to_input_weights     2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                         cell_to_input_weights          1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
+     *                                         cell_to_forget_weights         1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         cell_to_output_weights         1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         input_gate_bias                1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
+     *                                         projection_weights             2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                         projection_bias                1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
+     *                                         input_layer_norm_coefficients  1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         forget_layer_norm_coefficients 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         cell_layer_norm_coefficients   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                         output_layer_norm_coefficients 1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
      * @param[in]  activation_info             Contains activation information described in @ref ActivationLayerInfo.
-     * @param[in]  cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
-     * @param[in]  projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     * @param[in]  cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0f then clipping is disabled.
+     * @param[in]  projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
+     *                                         If set to 0.0f then clipping is disabled.
      */
     void configure(const ICLTensor *input,
                    const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights,
@@ -98,35 +104,40 @@
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLLSTMLayer
      *
-     * @param[in] input                       Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
-     * @param[in] input_to_forget_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] input_to_cell_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] input_to_output_weights     2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] recurrent_to_cell_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     * @param[in] forget_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in] cell_bias                   1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in] output_gate_bias            1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     * @param[in] output_state_in             2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
-     * @param[in] cell_state_in               2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
-     * @param[in] scratch_buffer              2D tensor with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF. Data type supported: Same as @p input.
-     * @param[in] output_state_out            2D weights tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
-     * @param[in] cell_state_out              2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
-     * @param[in] output                      Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].
-     *                                        Data types supported: Same as @p input.
-     * @param[in] lstm_params                 (Optional) Weights tensors used in peephole optimization:
-     *                                        input_to_input_weights       2D weights tensor with dimensions [input_size, num_units]. Data type supported: Same as @p input.
-     *                                        recurrent_to_input_weights   2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     *                                        cell_to_input_weights        1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
-     *                                        cell_to_forget_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     *                                        cell_to_output_weights       1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input.
-     *                                        input_gate_bias              1D weights tensor with dimensions [num_units]. Data type supported: Same as @p input
-     *                                        projection_weights           2D weights tensor with dimensions [output_size, num_units]. Data type supported: Same as @p input.
-     *                                        projection_bias              1D weights tensor with dimensions [output_size]. Data type supported: Same as @p input.
+     * @param[in] input                       Source tensor info. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: F16/F32.
+     * @param[in] input_to_forget_weights     2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] input_to_cell_weights       2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] input_to_output_weights     2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_cell_weights   2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     * @param[in] forget_gate_bias            1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] cell_bias                   1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] output_gate_bias            1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     * @param[in] output_state_in             2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state_in               2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] scratch_buffer              2D tensor info with dimensions [num_units * 4, batch_size] with CIFG or [num_units * 3, batch_size] without CIGF.
+     *                                        Data type supported: Same as @p input.
+     * @param[in] output_state_out            2D weights tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input.
+     * @param[in] cell_state_out              2D tensor info with dimensions [num_units, batch_size]. Data type supported: Same as @p input.
+     * @param[in] output                      Destination tensor info. Output is a 2D tensor with dimensions [output_size, batch_size]. Data types supported: Same as @p input.
+     * @param[in] lstm_params                 (Optional) Weights tensors info used in peephole optimization:
+     *                                        input_to_input_weights         2D weights tensor info with dimensions [input_size, num_units]. Data type supported: Same as @p input.
+     *                                        recurrent_to_input_weights     2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                        cell_to_input_weights          1D weights tensor info with dimensions [num_units]. Can be nullptr. Data type supported: Same as @p input.
+     *                                        cell_to_forget_weights         1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        cell_to_output_weights         1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        input_gate_bias                1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input
+     *                                        projection_weights             2D weights tensor info with dimensions [output_size, num_units]. Data type supported: Same as @p input.
+     *                                        projection_bias                1D weights tensor info with dimensions [output_size]. Data type supported: Same as @p input.
+     *                                        input_layer_norm_coefficients  1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        forget_layer_norm_coefficients 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        cell_layer_norm_coefficients   1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
+     *                                        output_layer_norm_coefficients 1D weights tensor info with dimensions [num_units]. Data type supported: Same as @p input.
      * @param[in] activation_info             Contains activation information described in @ref ActivationLayerInfo.
-     * @param[in] cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0 then clipping is disabled.
-     * @param[in] projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.
+     * @param[in] cell_threshold              The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. If set to 0.0f then clipping is disabled.
+     * @param[in] projection_threshold        The clipping threshold for the output from the projection layer, such that values are bound within [-proj_clip, proj_clip].
+     *                                        If set to 0.0f then clipping is disabled.
      *
      * @return a status
      */
@@ -145,23 +156,16 @@
 private:
     CLMemoryGroup                        _memory_group;
     CLFullyConnectedLayer                _fully_connected_input_gate;
-    CLGEMM                               _gemm_input_gate;
-    CLTransposeKernel                    _transpose_input_gate;
-    CLSaturatedArithmeticOperationKernel _accum_input_gate1;
-    CLArithmeticAddition                 _accum_input_gate2;
+    CLArithmeticAddition                 _accum_input_gate1;
     CLSaturatedArithmeticOperationKernel _subtract_input_gate;
     CLPixelWiseMultiplicationKernel      _pixelwise_mul_input_gate;
     CLActivationLayerKernel              _activation_input_gate;
     CLFullyConnectedLayer                _fully_connected_forget_gate;
-    CLGEMM                               _gemm_forget_gate;
-    CLTransposeKernel                    _transpose_forget_gate;
-    CLSaturatedArithmeticOperationKernel _accum_forget_gate1;
-    CLArithmeticAddition                 _accum_forget_gate2;
+    CLArithmeticAddition                 _accum_forget_gate1;
     CLPixelWiseMultiplicationKernel      _pixelwise_mul_forget_gate;
     CLActivationLayerKernel              _activation_forget_gate;
     CLFullyConnectedLayer                _fully_connected_cell_state;
     CLGEMM                               _gemm_cell_state1;
-    CLGEMM                               _gemm_cell_state2;
     CLTransposeKernel                    _transpose_cell_state;
     CLSaturatedArithmeticOperationKernel _accum_cell_state1;
     CLSaturatedArithmeticOperationKernel _accum_cell_state2;
@@ -170,17 +174,12 @@
     CLActivationLayerKernel              _cell_clip;
     CLPixelWiseMultiplicationKernel      _pixelwise_mul_cell_state2;
     CLFullyConnectedLayer                _fully_connected_output;
-    CLGEMM                               _gemm_output;
     CLPixelWiseMultiplicationKernel      _pixelwise_mul_output_state1;
-    CLTransposeKernel                    _transpose_output;
-    CLSaturatedArithmeticOperationKernel _accum_output1;
-    CLArithmeticAddition                 _accum_output2;
+    CLArithmeticAddition                 _accum_output1;
     CLActivationLayerKernel              _activation_output;
     CLActivationLayerKernel              _activation_output_state;
     CLPixelWiseMultiplicationKernel      _pixelwise_mul_output_state2;
     CLFullyConnectedLayer                _fully_connected_output_state;
-    CLGEMM                               _gemm_output_state;
-    CLSaturatedArithmeticOperationKernel _accum_output_state;
     CLActivationLayerKernel              _projection_clip;
     CLCopyKernel                         _copy_cell_state;
     CLCopyKernel                         _copy_output;
@@ -190,6 +189,18 @@
     CLWidthConcatenate2TensorsKernel     _concat_weights_input_gate;
     CLWidthConcatenate2TensorsKernel     _concat_weights_output;
     CLMemsetKernel                       _ones_memset_kernel;
+    CLMeanStdDevNormalizationLayer       _mean_std_norm_input_gate;
+    CLPixelWiseMultiplicationKernel      _pixelwise_mul_input_gate_coeff;
+    CLSaturatedArithmeticOperationKernel _accum_input_gate_bias;
+    CLMeanStdDevNormalizationLayer       _mean_std_norm_forget_gate;
+    CLPixelWiseMultiplicationKernel      _pixelwise_mul_forget_gate_coeff;
+    CLSaturatedArithmeticOperationKernel _accum_forget_gate_bias;
+    CLMeanStdDevNormalizationLayer       _mean_std_norm_cell_gate;
+    CLPixelWiseMultiplicationKernel      _pixelwise_mul_cell_gate_coeff;
+    CLSaturatedArithmeticOperationKernel _accum_cell_gate_bias;
+    CLMeanStdDevNormalizationLayer       _mean_std_norm_output_gate;
+    CLPixelWiseMultiplicationKernel      _pixelwise_mul_output_gate_coeff;
+    CLSaturatedArithmeticOperationKernel _accum_output_gate_bias;
     CLTensor                             _input_gate_out1;
     CLTensor                             _input_gate_out2;
     CLTensor                             _input_gate_out3;
@@ -212,12 +223,21 @@
     CLTensor                             _cell_state_activation;
     CLTensor                             _output_state1;
     CLTensor                             _ones;
+    CLTensor                             _input_layer_norm_out1;
+    CLTensor                             _input_layer_norm_out2;
+    CLTensor                             _forget_layer_norm_out1;
+    CLTensor                             _forget_layer_norm_out2;
+    CLTensor                             _cell_layer_norm_out1;
+    CLTensor                             _cell_layer_norm_out2;
+    CLTensor                             _output_layer_norm_out1;
+    CLTensor                             _output_layer_norm_out2;
     bool                                 _run_peephole_opt;
     bool                                 _run_cifg_opt;
     bool                                 _perform_cell_clipping;
     bool                                 _has_projection_weights;
     bool                                 _perform_projection_clipping;
     bool                                 _is_prepared;
+    bool                                 _is_layer_norm_lstm;
 };
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_CLLSTMLAYER_H__ */