Wording updates and grammar check

Author: fulldecent

Formant Analyzer/Formant Analyzer/FormantPlotView.swift

@@ -18,7 +18,7 @@ class FormantPlotView: UIView {
             view.removeFromSuperview()
         }
 
-        // Now, we add an image to current view to plot location of first two formants
+        // Now, we add an image to current view to plot location of the first two formants
         let backgroundRect = CGRect(x: 0, y: 0, width: self.frame.size.width, height: self.frame.size.height)
         let backgroundImageView = UIImageView(frame: backgroundRect)
         backgroundImageView.image = UIImage(named: "vowelPlotBackground.png")

Formant Analyzer/Formant Analyzer/SpeechAnalyzer.swift

@@ -101,7 +101,7 @@ class SpeechAnalyzer {
     }
 
     //
-    //MARK: Class functions that allow tweaking the parameters
+    //MARK: Class functions that allow tweaking of parameters
     //
 
     /// Analyzes a signal to find the significant part
@@ -355,7 +355,7 @@ class SpeechAnalyzer {
 // Must be able to represent an empty range
 extension CountableRange where Bound.Stride == Int {
     /// Shrink range by `portion` of its length from each size
-    /// - Parameter portion a fraction in the range 0...0.5
+    /// - Parameter portion is a fraction in the range 0...0.5
     func truncatedTails(byPortion portion: Double) -> CountableRange<Bound> {
         let start = self.lowerBound.advanced(by: Int((portion * Double(self.count)).rounded()))
         let end = self.lowerBound.advanced(by: Int(((1 - portion) * Double(self.count)).rounded()))

Formant Analyzer/Formant Analyzer/ViewController.swift

@@ -178,7 +178,7 @@ class FirstViewController: UIViewController {
             return String(format: "%.02f", value)
         }
         self.lineChartFull.valueLabelPosition = .left
-        // Number of visible step in the chart
+        // Number of visible steps in the chart
         self.lineChartFull.verticalGridStep = 3
         self.lineChartFull.horizontalGridStep = 5
         // Margin of the chart

Formant Analyzer/Pods/FSLineChart/README.md

@@ -2,7 +2,7 @@ Audio Format Conversion
 =======================
 
 The prerecorded utterances are converted into a standardized format for
-processing in Matlab. To ensure identical results with offline processing as
+processing in Matlab. To ensure identical results with offline processing and
 when using the Formant Analyzer iOS app, we have chosen a very simple preferred
 format for storing the audio.
 

Offline MATLAB analysis/2. Audio Format Conversion/README.md

@@ -4,7 +4,7 @@
 %  - Raw audio samples
 %  - 44 100 Hz sample rate
 %  - Mono channel
-%  - 16-bit signed integer samples written little-endian
+%  - 16-bit signed integer samples written in little-endian format
 %
 
 recordings = {'arm', 'beat', 'bid', 'calm', 'cat', 'four', 'who'};

Offline MATLAB analysis/2. Audio Format Conversion/main.m

@@ -25,7 +25,7 @@ And the chosen constants are given as:
 
 -   `TRIM_FACTOR` = 0.15;
 
-**Warning: The results of this algorithm should be off by one compared to the
+**Warning: The results of this algorithm should be off-by-one compared to the
 iOS project because Matlab counts indices starting with 1 but Swift counts starting with 0.**
 
 Analysis

Offline MATLAB analysis/3. Vowel Isolation/README.md

@@ -1,6 +1,6 @@
 %% VOWEL ISOLATION
 % We process all recordings to isolate just the vowel sound
-% Then we play the two original and the isolation back-to-back
+% Then we play the original and the isolation back-to-back
 %
 
 recordings = {'arm', 'beat', 'bid', 'calm', 'cat', 'four', 'who'};

Offline MATLAB analysis/3. Vowel Isolation/play.m

@@ -1,6 +1,6 @@
 %% VOWEL ISOLATION
 % We process all recordings to isolate just the vowel sound
-% Then we play the two original and the isolation back-to-back
+% Then we play the original and the isolation back-to-back
 %
 
 recordings = {'arm', 'beat', 'bid', 'calm', 'cat', 'four', 'who'};

Offline MATLAB analysis/3. Vowel Isolation/show.m

@@ -1,7 +1,7 @@
 This work compared LPC coefficients and roots of prediction filters obtained
 from MATLAB and objective-C.
 
-There is slight mismatch, most probably due to MATLAB implying windowing and us
+There is a slight mismatch, most probably due to MATLAB implying windowing and us
 not including that step.
 
 Comparison of LPC Coefficients

Offline MATLAB analysis/4. LPC Formant Estimation/LPC Compare MATLAB and XCODE.md

@@ -29,7 +29,7 @@ periodic signal which does not go to zero at the beginning and end.**
 Analysis
 ========
 
-You can perform this analysis using by running `estimateFormants.m`.
+You can perform this analysis by running `estimateFormants.m`.
 
 Following are the transfer functions for each recording.
 

Offline MATLAB analysis/4. LPC Formant Estimation/README.md

@@ -99,7 +99,7 @@ particularly from Figure 4. We can see that if a speech signal does not change
 over the duration of observation, the formant frequencies remain stable and we
 get a tight cluster (4th cluster). On the other hand, if speech sample is short
 and surrounded by consonants, we get poor results (3rd cluster). In general, the
-clusters are well spread and we need to perform post processing on the results
+clusters are well spread and we need to perform post-processing on the results
 of all speech segments present in a vowel sound.
 
 Now, we are in a good position to estimate the effort required for real-time

Offline MATLAB analysis/Feasibility/README.md

@@ -11,7 +11,7 @@ Project Scope and Updates
 The project started with an original motivation to "recognize words, recognize a
 string of words and identify a voice." [At first, the approach
 was](<https://www.clear.rice.edu/elec431/projects96/digitalbb/original_proposal.html>)
-to use continious wavelet transform to do wavelet analysis for recognizing
+to use continuous wavelet transform to do wavelet analysis for recognizing
 vowels however, [this was quickly
 updated](<https://www.clear.rice.edu/elec431/projects96/digitalbb/new_proposal.html>)
 to target formant analysis and pitch determination with a new goal of