whisper : minor fixes (ggerganov#1154)

README.md

@@ -61,7 +61,7 @@ Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
 - Various other examples are available in the [examples](examples) folder
 
 The tensor operators are optimized heavily for Apple silicon CPUs. Depending on the computation size, Arm Neon SIMD
-instrisics or CBLAS Accelerate framework routines are used. The latter are especially effective for bigger sizes since
+intrinsics or CBLAS Accelerate framework routines are used. The latter are especially effective for bigger sizes since
 the Accelerate framework utilizes the special-purpose AMX coprocessor available in modern Apple products.
 
 ## Quick start

whisper.cpp

@@ -82,7 +82,7 @@ static void byteswap_tensor(ggml_tensor * tensor) {
  } while (0)
 #define BYTESWAP_TENSOR(t) \
  do { \
- byteswap_tensor(tensor); \
+ byteswap_tensor(t); \
  } while (0)
 #else
 #define BYTESWAP_VALUE(d) do {} while (0)
@@ -589,7 +589,7 @@ struct whisper_model {
 struct whisper_sequence {
  std::vector<whisper_token_data> tokens;
 
- // the accumulated transcription in the current interation (used to truncate the tokens array)
+ // the accumulated transcription in the current iteration (used to truncate the tokens array)
  int result_len;
 
  double sum_logprobs_all; // the sum of the log probabilities of the tokens

whisper.h

@@ -346,7 +346,7 @@ extern "C" {
  void * user_data);
 
  // Parameters for the whisper_full() function
- // If you chnage the order or add new parameters, make sure to update the default values in whisper.cpp:
+ // If you change the order or add new parameters, make sure to update the default values in whisper.cpp:
  // whisper_full_default_params()
  struct whisper_full_params {
  enum whisper_sampling_strategy strategy;